Categories   >   OLAP Tools
Last Reviewed: November 26th, 2024

Best OLAP Tools Of 2024

What are OLAP Tools?

OLAP tools are akin to super-powered spreadsheets for analyzing massive datasets. Imagine a giant warehouse full of sales data, organized by region, product, and time. Traditional tools might struggle, but OLAP lets you slice and dice this data from any angle. Need to see how furniture sales compare across states over the past year? OLAP can handle it. This helps businesses solve major challenges by uncovering hidden trends, spotting sales opportunities, and making data-driven decisions. Benefits include improved forecasting accuracy, better product positioning, and a deeper understanding of customer behavior. OLAP tools offer features like drill-down (zooming into specific data points), roll-up (summarizing data across categories), and pivot tables (reorganizing data for different views). Emerging features include cloud-based deployment for scalability and integration with artificial intelligence for even richer insights. OLAP benefits users in finance, sales, marketing, and any data-driven department across various industries. A limitation is that complex queries can take time to process. Overall, OLAP tools empower businesses to unlock the true potential of their data, transforming information into strategic advantages.

What Are The Key Benefits of OLAP Tools?

  • Faster Insights from Data
  • Improved Data Exploration
  • Advanced Trend Analysis
  • More Accurate Forecasting
  • Better Decision Making
  • Identify Hidden Patterns
  • Support Strategic Planning
  • Optimize Product Positioning
  • Deeper Customer Understanding
Read more

Overall

Based on the latest available data collected by SelectHub for 168 solutions, we determined the following solutions are the best OLAP Tools overall:

Tableau
Tableau
Start Price
$15
Per User, Monthly
Company Size
Small Medium Large
Deployment
Cloud On-Premise
Platform
Mac Windows Linux Chromebook Android
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Why We Picked Tableau

Tableau Desktop is a BI solution for data visualization, dashboarding and location analysis. In online reviews, users said they found its drag-and-drop charting a boon for creating charts and maps. Regarding customization, many users praised the platform for its various labeling and design options.

I recently tried the Tableau Desktop 2024.1.3 version. The trial is only for 14 days and is enough for a sneak peek into Tableau’s dashboarding and data storytelling capabilities. For more straightforward use cases, Tableau is incredibly user-friendly and fast. Creating a new sheet gives you a canvas to create a visualization. Once you have the required sheets, combining them into a dashboard view is straightforward — select and add.

My dataset included healthcare data, including details of patients, their hospital visits and insurance payer details. One use case was to find the total claim settlement amount. I dragged the Total Claims Cost and Payer fields to the column and row shelves, and Tableau gave me a bar graph. The toolbar had single-click options for sorting data from increasing to decreasing values or the other way around.

To view the number of encounters by payer, I dragged the Payer field to the row shelf and used the SUM(ROW_COUNT()) function on the column shelf. The chart popped up with more visualization and layout options.

I wanted an interactive filter to view the average claim cost by birthdate. I dragged the Birthdate field to the Filters shelf and right-clicked on it to set the end date as October 22, 1961. Selecting Show Filter added a slider conveniently to the right of my visualization. I could see the data for people born before October 22, 1961, and if required, I could change the end date.

Another use case would be viewing the data by the type of hospital visits — how many people were inpatients, outpatients or those who needed emergency care. I dragged and dropped the Total Claims Cost and Payer fields into columns and rows, respectively. Similarly, I dropped Encounterclass into the Filters shelf and clicked on Show Filter to enable a checkbox on the screen. It had all the categories of visits, giving users the option to select the desired views.

One-fourth of the users discussing adoption said there was a steep learning curve. Tableau relies on Python and R scripts for statistics in its visualizations. It's where the named licenses can prove to be a blessing, as you can opt to train upcoming Creators and Explorers. We recommend factoring in training if you want to hit the ground running.

Some reviewers felt discounted packages for business editions should be available, similar to the free student licenses. At $70 per user, the Creator license can seem costly when compared to Power BI ($9.99 per user) and Qlik Sense ($30 per user).

Here's the good news, though. Its built-in user management acts as a permissions layer for your organization - users can only access the relevant content. Plus, an organization will have very few Creators and a greater number of Viewers and Explorers, and the license fee reduces from Creator to Explorer to Viewer.

We recommend opting for a wise license combination to get the most out of the product.

On the upside, the vendor constantly releases new features, the latest one being Einstein CoPilot in beta.

Overall, Tableau is a competitive BI solution, but if the pricing seems inflexible, quite a few other solutions offer live insights and advanced analytics out of the box.

Pros & Cons

  • Data Visualization: Almost 98% of users who reviewed its visual capabilities praised the platform for its dashboards and the freedom to play around with data and modify charts as desired.
  • User-Friendly: According to 93% of users who mentioned ease of use, it makes data accessible with its easy user actions and handy tooltips.
  • Data Connectivity: About 92% of users who discussed data sourcing praised its ability to pull data from disparate systems.
  • Pricing: Around 90% of the users citing cost found it expensive.
  • Speed: About 71% of the users who discussed performance found it slow when processing large data volumes.
  • Onboarding Woes: Approximately 67% of the users who reviewed the platform's adoption said there was a steep learning curve.

Key Features

  • Connectors: Combine data from various sources by choosing from a wide range of connectors — no need to spend on expensive third-party data integration tools. Tableau Bridge connects private networks to live data sources via Tableau Cloud.
  • AI: Tableau now offers AI capabilities thanks to Einstein Analytics.
    • Tableau Pulse: Explore data independently and ask questions with AI analytics. Tableau Pulse is available with Tableau Cloud and Embedded Analytics.
    • Explain Data: Understand the displayed insights with natural language explanations of data points.
    • Einstein CoPilot (Beta): Close the gap in understanding data with AI insights. Discover hidden trends by asking follow-up questions without losing context, thanks to generative AI. Einstein CoPilot is available with a Tableau Cloud subscription.
  • Tableau Prep: Clean and transform data of all types, including survey results, feedback data and social media posts. Shape and combine it with Tableau Prep, which is available with the paid edition only.
  • Data Stories: Convey your message with compelling narratives to get stakeholder buy-in. Drag and drop sheets onto the storyboard to show the growth, decline or stability of critical metrics.
  • Animations: Explain how data changes over time with animated charts and customize them to include graphics, labels and colors.
  • Filtering: Focus on the data that matters; it’s as easy as dragging and dropping desired fields to the Filter shelf. Specify a value range, set a condition or choose the top values to display.
  • User-Based Licenses: Explore cost-effective license combinations that work for your team.
    • Creators can build dashboards, permissions, and governance rules, and establish connections to new sources. They’re content authors who transform and analyze data. This license is available at $70 per user monthly, billed annually. However, they can’t control the Tableau Server or Desktop environment.
    • Explorer licenses are suitable for line-of-business users whose role requires independent data exploration. They can author content but within a governed ecosystem. Each Explorer license costs $42 monthly, billed annually. They can’t connect to new sources, modify data, or use the Tableau desktop or custom SQL.
    • Viewers can interact with data, apply filters and follow pre-decided workflows. This license is available for $15 per user monthly, billed annually. Viewers have limited rights and can’t create and edit visualizations and the underlying data.
Power BI
Power BI
Start Price
$10
Per User, Monthly
Company Size
Small Medium Large
Deployment
Cloud On-Premise
Platform
Mac Windows Linux Chromebook Android
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Why We Picked Power BI

Our researchers ranked products on a whole bunch of features. They include data management, querying and visualization, advanced and embedded analytics, mobile BI, and IoT and location analytics.

In our rankings, Power BI scores 87 for connectivity, leaving behind Tableau, Oracle Analytics and Dundas BI. Robust Microsoft technology is one reason, for sure. Besides, intelligent techniques like DirectQuery and easy data modeling make it popular among users.

In product reviews, some users mentioned a lag when sharing reports from the desktop to the cloud. For me, the platform was a tad slow to start, but otherwise, it stayed performant for my average-sized dataset.

When dealing with sales data, total sales, the top-performing products, seasonality and period trends are common queries. Creating a sales KPI report in Power BI was an excellent way for me to answer them. My CSV files included sales, calendar, products and store data.

Connecting to sources is straightforward with Get Data on the home screen and toolbar. Once I had pulled in the data, I clicked on Transform Data and opened the Power Query editor. It automatically detects the data type for strings and numbers but can get confused with dates and currency, which it marks as text. It involved some manual wrangling, but I had it sorted in no time. Read my article on KPI Reports to learn how I did it.

But I wouldn’t call it a deal-breaker as it’s not a tedious task. I had the same experience with Qlik Sense, but Tableau was way better as it recognizes seven data types — string, number, date, date and time, boolean, geographic and cluster values.

Tracking sales over periods required a greater level of detail, so I added new columns to the calendar data — start of month and start of week. Column statistics were immensely helpful in identifying unique, distinct and null values and correcting incomplete records. Clicking on the number of products selling at a particular price allowed me to see which toys sold at that price.

Creating a relational data model by defining primary keys is a manual process and seems dated once you’ve used Qlik Sense. Adding calculated measures is where DAX shows its magic. For data workers well-versed with SQL, DAX is a ready-to-go tool they’ll be glad to have in their corner.

Creating visualizations wasn’t as intuitive as Tableau as it involved drag-and-drop onto the canvas, and frankly, I felt like I was flying blind. I didn’t feel that way with Tableau, and it’s slicker.

Power BI offers a paintbrush tool that lets you define the layout, the card arrangement and the maximum number of cards. You can define the canvas settings, background and headers and determine the filter pane settings. It took me longer to create a dashboard from scratch than it took in Tableau.

Some users found the pricing structure too complex. While using Azure data in Power BI for basic queries is free, costs can add up when you go for text and sentiment analysis. With Microsoft Fabric, the pricing complexity is set to rise. Though Power BI is available separately too, you’ll need to rely on Fabric to manage users, licenses and other administrative tasks.

About 31% of the users mentioning cost complained about onboarding difficulties, possibly because DAX introduces the complexity of learning syntax. It can daunt non-technical users initially, but guided formulas can make the task easier. That said, I agree with the majority of user reviews that training will speed up onboarding and help your team maximize the investment.

Overall, Power BI has many powerful features and will give you value for your money. If you’re not a Microsoft user yet, it’s worth checking out for the baked-in vendor technologies like Azure and SSAS. If you are an MS user, Power BI might be a no-brainer, though be prepared to shell out a little extra for advanced functionality and additional modules.

Pros & Cons

  • Integrations: Around 95% of users who mentioned data sources said they were satisfied with its flexibility in connecting to sources.
  • Data Visualization: About 93% of the users who discussed visual analysis said they relied on it for daily reporting.
  • Functionality: Over 75% of the users reviewing features said they were impressed with its live queries, DAX calculations and data modeling.
  • Ease of Use: Approximately 72% of the users who mentioned its UI said it was straightforward to use.
  • Speed: About 95% of recent reviews citing performance said the platform lagged when dealing with large data volumes.
  • Adoption: Around 81.5% of the reviewers mentioning adoption said the learning curve was steep.
  • Cost: Approximately 71% of users discussing pricing complained about the platform being expensive.

Key Features

  • Dataflows: Save time with reusable workflows that lock the logic in. While shared datasets are open to interpretation, dataflows will take your users in one direction only, ensuring consistent results. It’s like a written recipe, just follow the steps to get the taste right.
  • Analyze in Excel: Focus on the end game. Give your teams the freedom to analyze their data in Excel and move the results back to Power BI.
  • DAX: Empower your people to go beyond raw data. Derive calculated columns and measures with Data Analysis Expressions. Watch them update as you apply filters and slicers and interact with data in other ways.
  • Data Alerts: Act in time to keep things running smoothly. Stay informed of changes with alerts. Subscribe to receive notifications via email or the Power BI notification center (available only with Power BI Service). Among visualizations, KPI cards, cards and gauges have the alert option. 
  • Data Refreshes: Stay ahead of trends with the latest insight. Update data on demand in Power BI or schedule refreshes with Power Automate. Power BI Pro and Premium allow up to eight and 48 refreshes daily, respectively.
  • Key Influencers Visual: Decide the next steps by spotting the factors affecting a critical metric. As a transporter, does only the terrain impact how consistently your trucks deliver, or is the average age of the fleet vehicles also a factor?
  • Decomposition Tree: Identify which product category or region contributed most to sales increase or decrease. For instance, you can analyze sales trends by channel with the decomposition tree.

Pricing

License/Subscription Cost
  • Based on the number of users for Power BI Pro and capacity-based pricing for Power BI Premium
Maintenance Cost
  • Included in the subscription cost
Installation/Implementation Cost
  • Included in the subscription cost. Additional charges may apply for data migration during implementation of Power BI, maintaining on-premise data sources and building dashboards and reports
Customization Cost
  • Dependent on functional requirements and specific needs of the organization
Data Migration Cost/Change Management/Upfront Switching Cost
  • Dependent on your current software, amount of data to be migrated, availability of migration tools, complexity of data and gaps between the existing system and the new system.
Recurring/Renewal Costs
  • Renewal cost is included in the fees paid monthly or annually
Mathematica
Mathematica
Start Price
$1,800
Annually
Company Size
Small Medium Large
Deployment
Cloud On-Premise
Platform
Mac Windows Linux Chromebook Android
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Why We Picked Mathematica

Let's crunch some numbers and see what users have to say about Mathematica!

Mathematica has garnered a reputation as a powerful computational tool, particularly in academic and research settings. Users frequently praise its symbolic computation capabilities, allowing them to manipulate and solve complex mathematical expressions and equations with ease. This strength sets Mathematica apart from competitors like MATLAB, which primarily focuses on numerical computation. Mathematica's notebook interface also receives positive feedback for its ability to combine code, visualizations, and text in a single document, facilitating reproducible research and clear communication of findings. However, Mathematica's steep learning curve and high price point are often cited as drawbacks. Users transitioning from other programming languages may find Mathematica's syntax and functional programming paradigm challenging to grasp initially. Additionally, the cost of a Mathematica license can be prohibitive for individual users or small businesses.

Overall, Mathematica is best suited for researchers, scientists, and engineers who require a comprehensive tool for symbolic and numerical computation, data analysis, and visualization. Its extensive functionality and ability to handle complex mathematical problems make it an invaluable asset in these fields. However, individuals or organizations with limited budgets or those seeking a more user-friendly option may want to explore alternative software solutions. Keep in mind that software is constantly evolving, so it's always a good idea to check for the latest updates and user reviews to make an informed decision.

Pros & Cons

  • Symbolic Computation: Mathematica excels at handling and manipulating symbolic expressions, making it ideal for tasks that involve algebra, calculus, and other forms of mathematical analysis. This can be particularly useful for financial modeling, risk analysis, and other business intelligence applications that require complex calculations.
  • Visualization Capabilities: Mathematica offers a wide range of visualization tools that can be used to create high-quality charts, graphs, and other visual representations of data. These visualizations can be interactive, allowing users to explore data from different perspectives and gain deeper insights. This is essential for effectively communicating complex data to stakeholders in a business setting.
  • Automation and Scripting: Mathematica allows users to automate tasks and create scripts, which can save time and improve efficiency. This can be particularly useful for repetitive tasks, such as data cleaning and analysis. Automating these tasks can free up time for business intelligence professionals to focus on more strategic initiatives.
  • Machine Learning and AI: Mathematica includes a wide range of machine learning and artificial intelligence (AI) tools that can be used for tasks such as predictive modeling, classification, and anomaly detection. These capabilities are becoming increasingly important for business intelligence, as they can help organizations to identify trends, make better decisions, and gain a competitive advantage.
  • Price: Mathematica comes with a hefty price tag, especially for commercial use, which can be a significant barrier for individuals or small businesses.
  • Learning Curve: The software has a steep learning curve due to its vast functionality and unique syntax, requiring a significant time investment to master.
  • Closed Ecosystem: Mathematica operates within a closed ecosystem, making it challenging to integrate with other data analysis tools or programming languages commonly used in business intelligence.
  • Limited Collaboration: Collaboration features are not as robust as those found in other business intelligence platforms, hindering teamwork and knowledge sharing.
  • Visualization Capabilities: While Mathematica offers visualization tools, they may not be as intuitive or user-friendly as dedicated data visualization software, potentially limiting the ability to create compelling and insightful dashboards.

Key Features

  • Wolfram Language: Wolfram’s proprietary computational language allows developers to code with a language that allows both computers and humans to communicate with each other through almost 6,000 built-in functions. Built on a philosophy of knowledge-based programming, it aims to help users automate as much as possible and maximize coherence of design while being universally deployable in any environment.
  • Connect to Everything: Through symbolic expressions, interactions and external connections, the Wolfram Language conveniently connects to a broad spectrum of platforms, languages, databases, protocols, APIs, applications, file formats and devices.
  • Notebook Interface: With structured documents that store text, runnable code, dynamic graphics and more, Wolfram Notebooks provide an environment for technical workflows that supports interactive computation. They empower user literacy in a high-level programming interface through interactive coding, natural language queries and expansive documentation that make the platform accessible to users without coding experience.
  • AlgorithmBase: Not just through industrial-strength algorithms but also meta-algorithms and super functions, which automatically select the optimal algorithms to use in a given situation, users can define their goals or concepts and let the system take over to automatically achieve them, enabling discoveries and experimentation with algorithms. With its robust library of scalable and accurate algorithms, the AlgorithmBase serves as a trustworthy resource for programmers to use to ensure high-quality computations.
  • Data Visualization: Through algorithms, Mathematica can create visually compelling representations of data in the form of 2D and 3D plots, graphs, histograms, word clouds, geographic visualizations and more.
  • Machine Learning: Through highly automated functions that work on many types of data, the platform can carry out a wide range of tasks, including classifying data in categories, predicting values, learning from examples and performing automated time series analysis. 
  • Mathematica Online: Powered by the Wolfram Cloud, users can harness the computational system from directly within their web browsers, with no installation required. Everything automatically saves and stays in the cloud, and users can control who can access their documents through instant sharing, URL links and permissions controls. Seamlessly integrated with the desktop version, it allows users to upload or download notebooks and access the cloud from a computer.
  • Wolfram Knowledgebase: Mathematica and the Wolfram Language has access to the world’s largest and broadest trusted source of computable knowledge, curated by experts and derived from primary sources, including not just the data but also the methods that compute results.
  • Mobile App: The Wolfram Cloud free app for iOS and Android mobile devices allows users to edit, run and deploy programs and access Wolfram notebooks and instant apps through its home-screen-like experience.
Looker
Looker
Start Price
$2,900
Monthly
Company Size
Small Medium Large
Deployment
Cloud On-Premise
Platform
Mac Windows Linux Chromebook Android
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Why We Picked Looker

Looker is a forerunner in the business intelligence field for a reason; it generates reports that include easy sharing via link, automatic scheduling and a level of granular detail that allows for deeper analysis below the surface. It excels in its filter and drill-down features and creates unique URLs when users make changes to data, leading to enhanced sharing. However, one of its biggest strengths could also be considered one of its biggest weaknesses: its proprietary programming language, LookML which is used to construct SQL queries in the platform. While a flexible and powerful data querying language, of course, LookML isn’t the most accessible to non-technical users, which means that Looker requires an IT or data team to access its full capabilities and has a steep learning curve. Users also note that its data visualizations, while simple and easy to understand, are quite basic and lacking in customization options, particularly in comparison to competitors. Some users say that it may be more appropriate for internal reporting than presentation to shareholders and end-users because of its bare-bones visualization options. However, Looker truly shines when used by enterprises, with its scalability and data accessibility making it a stellar solution that can align departments and provide thousands of users access to data insights. Its price point reflects this, with its pricing being prohibitive to startups as about 88% of users who comment on its cost remark. Overall, Looker is a solid pick for larger businesses that have a team of power users who can maximize its functionality and set it up to deliver to employees across an entire organization.

Pros & Cons

  • Reporting: Looker features strong reporting features that offer a degree of granularity and scheduling that 100% of users who mention reporting evaluate as a strong benefit.
  • Support: Of the users who say they’ve contacted customer support, 95% say the team’s quick and informative responses are a plus.
  • Data Accessibility: All users who mention accessibility to data say Looker does this well, distributing insights to employees across departments and teams with ease, with 100% of users mentioning this feature believing it is a benefit.
  • Learning Curve: About 74% of users who touch on the platform’s ease of use say that the confusing documentation, lack of training opportunities and difficulty of using programming language make Looker a tough tool to pick up as a beginner.
  • Setup: Of the users who mention implementation, 81% say that setting up the platform is difficult, with integrations not being as plug-and-play as competitors and assistance from IT necessary to the setup process.
  • Speed: Approximately 87% of users who comment on the platform’s speed say that it is slow to render certain queries and often takes a while to load.
  • Functionality: About 78% of users who talk about Looker’s features say that they are left wanting many functions and find the ones that it does have limited in customization or too complex to use easily.

Key Features

  • Automated Modeling: Connects to relational databases and automatically generates models from the database schema.
  • Intuitive Visualizations: Generates visualizations in real time directly from the specified data source. Choose from an expansive library of visualization options like bar graphs, pie charts, Sankey diagrams, spider web charts, sunburst graphs, chord diagrams, heatmaps, funnels, treemaps and many more.
  • Time Zone Handling: Incorporates data seamlessly into the visualization, regardless of what time zone it is coming from.
  • LookML Data Modeling Language: Create scalable, reusable data models through the proprietary SQL-based data modeling language LookML.
  • Pre-Built Analytics Code: Use its Blocks feature as a starting point for building data analytics models with customizable code blocks. Includes optimized SQL patterns, custom visualization options, pre-built data models and more.
Qlik Sense
Qlik Sense
Start Price
$30
Monthly, Quote-based
Company Size
Small Medium Large
Deployment
Cloud On-Premise
Platform
Mac Windows Linux Chromebook Android
Request Pricing Request Demo

Why We Picked Qlik Sense

Qlik Sense focuses on independent data analysis for enterprises with advanced tools that include AI, natural language processing and automation. User reviews praise it for its associative engine, interactive visualizations and sophisticated analytics.

Its dataset-linking functionality gets my vote as the most significant differentiator since it makes data modeling seamless and saves time. In comparison, manually linking tables in Tableau and Power BI feels like a huge task.

It supports fewer features out of the box (69%) compared to Tableau (72%) and Power BI (74%), but this could be intentional. Qlik has ready-to-go modules for analytics, automation and printing, so keeping it lean is a smart vendor move. Users should be aware that additional modules will cost extra, though.

Qlik Sense SaaS is multi-cloud, so unless the admin assigns separate workspaces, your users won’t be able to create personal dashboards — everything is shared otherwise. Some users said the platform slowed when processing large workloads, which is a common issue with many other platforms. Assess your need for speed before committing to a purchase.

If upgrading from QlikView, you’ll need to create new objects initially, as both platforms have different architectures. However, the vendor assists in seamless migration with the Qlik Analytics Modernization program.

Overall, Qlik Sense is an efficient platform that offers many analysis capabilities worth considering. We recommend checking it out if you’re looking for an alternative to Power BI, entrenched in Microsoft technology, or Tableau, with its emphasis on visualization.

Pros & Cons

  • Integrations: Approximately 86% of users reviewing data sources were satisfied with its wide connectivity.
  • Ease of Use: About 84% of users who cited usability praised the platform for self-service BI.
  • Functionality: Around 80% of the reviews that mentioned features praised it for ETL and data visualization.
  • Data Visualization: About 66% of the users discussing dashboards were satisfied with its interactive displays that allowed them to dig deep.
  • Cost: About 87% of users who mentioned pricing found the tool expensive.
  • Performance: Around 86% of users citing speed said it lagged when processing large and complex datasets.
  • Training: Approximately 69% of users who discussed adoption said there was a significant learning curve.
  • Customization: Around 65% of users who mentioned the freedom to design dashboards said the tool offered limited options.

Key Features

  • AI Integration: Ask and answer questions in natural language and automate processes using OpenAI and H2O.ai. Feed massive datasets to the LLM and watch as it summarizes the insight for you. Move beyond traditional analysis by working with the IBM Watson API for natural language.
  • Qlik Sense Management Console: Develop apps, manage tasks and connections, and track performance. With QMC, create content and consume data insights.
  • Reporting Service: Keep partners and clients on the same page by sending reports to everyone involved, even non-Qlik users. Download reports, subscribe to charts and sheets, or automate report delivery with its Reporting Service, available with Qlik Sense Enterprise SaaS.
  • Apps: Create interactive dashboards and visualizations for separate tasks within Qlik Sense. An organization can use hundreds of Qlik Sense apps in its tech stack. 
  • Associative Recommendations: Save time defining how data tables relate with its intelligent suggestions, something Tableau and Power BI lack. Bubbles represent data tables and color-coded rings — green, orange and red — inside them indicate the possibility of links between the tables.

Pricing

License/Subscription Cost
On-Premise:
  • License fees include an upfront fee to own the software, plus IP for a fixed term, installation, customization and integration costs
  • Enterprise Edition is offered on-premise and is based on a token system
  • Based on a combination of server, user, document and application-based licensing
Cloud-Based/SaaS:
  • Based on recurring subscription-based model: $X per user, per month
Cost may vary depending on the Qlik Sense Pricing plan selected:
  • Cloud Basic, Cloud Business, Desktop, Enterprise Edition or Personal Edition
Maintenance Cost
On-Premise: Maintenance cost is over and above the upfront fee
Cloud-Based/SaaS: Maintenance cost is included in the service fees charged at the time of purchase
Installation/Implementation Cost
On-Premise: Included in the upfront cost/subscription cost
Cloud-Based/SaaS: None
Customization Cost
For both on-premise and cloud-based/SaaS, customization costs vary depending on the product and pricing tier chosen, and the level of customization requiredCosts will vary depending on the package selected
Recurring/Renewal Costs
On-Premise: Annual recurring fees to be paid over and above the upfront cost include annual renewal, upgrades and ongoing support
Cloud-Based/SaaS: A recurring monthly fee is charged, which typically includes maintenance, monitoring, upgrades, training and support
Spark
Spark
Company Size
Small Medium Large
Deployment
Cloud On-Premise
Platform
Mac Windows Linux Chromebook Android
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Key Features

  • Standalone Mode: Standalone mode is a web-based cluster manager for creating and distributing clusters on local machines, without using YARN or Apache Mesos. It can be used for local data processing or testing on a smaller scale. 
  • GraphX: A series of API that enable graph-parallel computation and graph generation within the system. It can accomplish ETL, iterative graphing and exploratory analysis. 
  • Machine Learning: The MLlib library enables machine learning at a big data level. It works with Python, R and Scala, and features machine learning pipeline construction and a community-supported set of algorithms. 
  • Distributed Datasets: Datasets are partitioned into smaller segments for distributed processing, called Resilient Distributed Datasets. RDDs are created by parallelizing a set or referencing an external one. 
  • Data Streaming: Spark Streaming is an extension that allows for a continuous data flow, enabling real-time analytics. It receives live data in a stream that it partitions into batches before sending it to the Spark Engine for processing through high-level abstraction called discretized stream.  
  • Integrations: Because it is open source, a vast community is constantly adding extensions and API to the core software. Spark can connect to virtually every mainstream data source, big data solution, warehouse/lake or visualization program. If the connector does not already exist, it could likely be developed. 
Funnel
Funnel
Start Price
$149
Monthly, Quote-based
Company Size
Small Medium Large
Deployment
Cloud On-Premise
Platform
Mac Windows Linux Chromebook Android
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Key Features

  • Custom Rules: Create rules to segment data based on specific needs, mitigating the need to write code. Leverage a point-and-click data prep toolbox to combine data or define custom metrics to answer business-specific questions. 
  • Currency Conversion: Automate currency conversion to facilitate side-by-side comparison across platforms and markets. 
  • Standard Rules: Use pre-built rules and logic to prepare data for analysis. Define standard naming conventions for dimensions and metrics. Combine traffic sources and segment data by the market or product sold. 
  • Data Explorer: Use the data explorer to explore data, perform ad hoc analysis, create reports and export them. 
  • KPI Reporting: Combine sales with advertising data to report on KPIs, including return on ad spend, revenue, conversion rate and more. Get a complete performance view at a deeper level to ensure profitability. 
QlikView
QlikView
Start Price
$2,500
Per User, Annual
Company Size
Small Medium Large
Deployment
Cloud On-Premise
Platform
Mac Windows Linux Chromebook Android
Request Pricing Request Demo

Why We Picked QlikView

QlikView is one of the foremost BI solutions in the market today, mainly due to the power of its associative query engine to link data from multiple sources that drives its visually impressive dashboards. With its strong data visualization capabilities, users can perform search and filter through data on-the-fly and conduct deep-dives to glean insights that matter to them. With a fast setup, users can have their first data model up and running in very little time. The software resides in-memory and houses data in RAM for quicker retrieval. With multi-tier access permissions for in-organization users, it enables users to view executive summaries at a glance, while allowing them to drill-down into data to find out more.
Sadly, Qlik is now scaling back on improvements and updates for QlikView and focusing on promoting QlikSense instead, a possible reason why its filter and search functions, ad-hoc reporting and graphics are lagging in terms of quality, as mentioned in many user reviews. Also, this platform can prove to be resource-heavy for databases housed on local machines, especially when performing batch update jobs. In addition to inflexible pricing plans and the cost of licensing, quite a few necessary add-ons are paid.
In summary, QlikView is one of the leading in-memory BI tools available in the market today and rates excellently with users in terms of data aggregation and visualization capabilities; however, buyers should factor in its pricing plans and other limitations when searching for the perfect BI solution for their enterprise.

Pros & Cons

  • Data Visualization: Approximately 80% of users who review its data visualization capabilities are satisfied with its intuitive drag-and-drop feature, rich libraries and its range of aesthetically appealing data representation options.
  • Data Preparation: Of users who mention data processing, 83% appreciate the platform’s seemingly limitless data transformation capabilities that help them deep-dive into all possible data relationships to glean actionable insights.
  • Functionality: Among users who share their views on this platform, around 68% say that they are satisfied with the power of its associative query engine that enables faster on-the-fly calculations and analytics aggregation at the speed of thought.
  • Sharing and Collaboration: About 83% of users who comment on sharing capabilities appreciate its multi-tier permissions capabilities and easy sharing of reports with clients via external sharing options.
  • Setup: Around 66% of users who mention ease of setup say that QlikView has a fast implementation cycle.
  • Cost: Pricing plans are inflexible and can be cost-prohibitive for small organizations and startups, though large organizations may find that it offers high value, as stated by 93% of users who mention its cost.
  • Performance: Approximately 42% of users say that performance-wise, this platform is resource-hungry and liable to slow down when crunching large amounts of data on local machines.
  • User Interface and Graphics: Of users who mention user interface, around 44% say that it needs improvement in deep-dive capabilities, as well as its quality of graphics.
  • Reporting: Of users who mention reporting, approximately 46% say that it lacks ad-hoc reporting and built-in reporting capabilities, requiring paid plugins to enhance the graphics quality of reports.

Key Features

  • Direct Data Source Connection: Connect to almost any data source, including cloud, big data, file-based and on-premise data. Pull information from many services (Salesforce, Hive, Teradata) and combine intel seamlessly into unique and intuitive dashboards.
  • Intelligent Visualization: Offer interactive displays and represent data in multiple ways for better data analysis. Flexible visualizations allow users to change and adjust graphics according to screen size.
  • Enterprise Collaboration: Facilitate collaboration for users to share the same dashboard, look at the same view or track one another as they navigate the application.
  • Strong Associations: Leverage the strength of the platform’s built-in association engine to conduct direct and indirect searches across data or within a single field. Identify data that is related and not associated.
  • Self-Service App Building: Build apps and files via the drag-and-drop function. Create individual lists with their visualization while managing and sharing across organizations.
  • Associative Indexing: Combine, transform and ingest data from multiple sources. Gathers data and indexes it to find logical associations. Explore and search big data repositories freely while keeping data intact.
  • Interactive Dashboards: Provide visualization capabilities and improve interaction using tooltip, lasso selection, filtering and drill-down functions. Encourage viewers to explore data by creating smart dashboards and distributing them using interactive elements.
  • In-Memory Application: House the software in memory, so conversions, queries and searches happen quicker and more efficiently. Eliminate problems that traditionally plague slow, on-disk applications. Locate all data in RAM.
  • Web Connectors: Extract data from multiple social networking sites and web-based sources using web APIs. Built-in connectors easily connect to any URL and fetch data.
  • Robust Data Controls: Enable meaningful data manipulation within the application by leveraging unique dashboards, reports and filter views.
  • Data Alerts: Spot anomalies and outliers by requesting context-aware alerts. Monitor and manage data without limitations.

Pricing

License/Subscription Cost Based on a combination of server, user, document and application-based licensing
Maintenance Cost
  • For On-Premise solution, maintenance cost is over and above the upfront fee
  • Standard support services are charged at 20% of the license cost
  • Premium (24X7) support services are charged at 23% of the license cost
    		•
    Installation/Implementation Cost Implementation services are provided by QlikView Consulting or through an implementation partner at an additional cost
    Customization Cost Will vary depending on the functional requirements or services chosen
    Data Migration Cost/Change Management/Upfront Switching Cost Dependent on your current software, amount of data to be migrated, availability of migration tools, complexity of data and gaps between the existing system and the new system.
    Training Cost
    • E-learning or self-learn modules are available free of cost on QlikView.com
    • All other trainings are charged based on volume. Live classroom training or online (virtual classroom) training is charged at $700 per person per day or $3,500 for a dedicated course (1 company) for up to 10 people
    Recurring/Renewal Costs Renewal costs includes software update license and support cost
    Spotfire
    Spotfire
    Start Price
    $0.99
    Monthly, Quote-based
    Company Size
    Small Medium Large
    Deployment
    Cloud On-Premise
    Platform
    Mac Windows Linux Chromebook Android
    Request Pricing Request Demo

    Why We Picked Spotfire

    In online reviews, Spotfire emerges as a user-friendly big data platform. Most users found data exploration easy with a drag-and-drop interface. Some users said the UI was dated, though, and said it could use a revamp. Most users praised its interactive visualizations and dashboards, saying they helped them interpret data better. But, a few said they would love to have more visuals to choose from.

    A user mentioned they did the calculations in Excel and imported them into Spotfire for visualization. It's a common scenario when a steep learning curve slows down adoption, and teams fall back on Excel. Most users said Spotfire takes time to learn. You might have to opt for a balance of multiple platforms to balance your departmental and enterprise needs.

    Spotfire surpasses Excel in data management, especially data prep. Customizable visualizations and custom Mods give you enough freedom to work within the platform.

    Though 72% of reviewers were happy with the integrations, Spotfire lacks some standard connectors, such as for Apache Kafka, forcing users to rely on workarounds.

    A majority of users found its pricing structure complex, especially as users increased. In such cases, organizations often tend to opt for a cheaper alternative for less advanced use cases while using the pricier platform for the critical ones. We advise doing a deep dive into the vendor's pricing plans to avoid making your tech stack top-heavy.

    Ultimately, Spotfire's appeal lies in its balance. It's visually captivating and user-friendly for casual users while offering enough depth for seasoned analysts. However, its pricing and learning curve might deter organizations on a tight budget.

    Pros & Cons

    • Data Visualization: About 86% of reviewers were satisfied with the available options when designing dashboards.
    • Support: Around 74% of users praised vendor support for their timely response and helpful attitude.
    • Integration: Almost 72% of users were satisfied that it integrates with their preferred systems.
    • Friendly Interface: Around 68% of reviewers said the platform was easy to use.
    • Functionality: About 64% of users said it had a rich feature set.
    • Cost: Around 96% of the user reviews said it the price was high and licensing complex.
    • Adoption: 90% of reviewers said there was a significant learning curve and users would need specialized knowledge of data science and statistics.

    Key Features

    • Spotfire Actions: Decide what to do with and act instantly — no need to switch to your procurement application to pause new orders. This powerful feature allows you to run scripts within analytics workflows. You can also trigger actions in your external system through visualization. Spotfire can set up over 200 commercial connections and has 1800 community connectors.
    • Mods: Build reusable workflows and visualization components, much like apps in Power BI and Qlik Sense. They allow your users to tailor their analytical processes so they don’t have to start from scratch every time. Based on code, they run in a sandbox with limited access to system resources for security. Users can share them through the Spotfire library. Mods improve efficiency and collaboration.
    • Batch Edits: Make similar changes to multiple files in one go. Write custom scripts to call the Spotfire API that’ll make changes to the files. Update the IronPython version to the latest one or embed the Spotfire JQueryUI library instead of its references.
    • Recurring Jobs: Simplify event scheduling to better manage your time and tasks. Improve efficiency and deliver reports at the same time on the same day of the week or month. The latest Spotfire version allows you to set recurring automation jobs to occur every X hours, days, weeks or months.
    • Web Player REST API: Share insight with clients and partners without them needing to sign up for a paid Spotfire account. Engage them via data visualizations on the web browser, thanks to Spotfire Web Player. Update analyses on the web with real-time data in the latest Spotfire version.
    • Roles: Invest wisely — opt for licenses that align with user roles. Choose Spotfire Analyst for data analysts, scientists and power users who need deep-dive analysis. Get the Business Author license for enterprise users, analysts and power users to create and consume insights without deep expertise. Choose consumer licenses for users who’ll interact with and consume data. They include the C-suite and non-technical users within the organization.
    • Information Designer: Prepare fully governed data sources for business users in a dedicated wizard. Set up their preferred data sources and define in advance how Spotfire will query and import data into storage. Specify which columns to load and which filters, joins and aggregations to apply.
    • Audio and Image Processing: Add user feedback from customer calls and videos. Interpret public sentiment about your product by analyzing social media pictures and videos. Spotfire enables writing code to extract text from audio and image files. You can then import the data into the platform for analysis.
    • IoT Analytics: Gain insight at lightning speed; build microservices and deploy them at the edge. With Spotfire, you can add IoT data to your regular data for the complete picture.
    Oracle Analytics Cloud
    Oracle Analytics Cloud
    Start Price
    $16
    Per User, Monthly
    Company Size
    Small Medium Large
    Deployment
    Cloud On-Premise
    Platform
    Mac Windows Linux Chromebook Android
    Request Pricing Request Demo

    Why We Picked Oracle Analytics Cloud

    Oracle Analytics Cloud is among the vendor’s many data services, including a business intelligence suite and a data intelligence platform. Besides, Oracle offers bespoke solutions for HCM, supply chain and customer experience. What differentiates Oracle Analytics is that extra dash of augmented capabilities.

    Embedded BI is where it truly shines, giving you natural language insights with a single click. This feature extends to its mobile app, and it outperforms many leading platforms with natural language queries and podcasts on mobile.

    According to our researchers, Oracle Analytics Cloud has fewer out-of-the-box features than its competitors, such as Power BI and Qlik Sense. Plus, licensing becomes complex when combining the database, middleware and analytics applications.

    It’s common for large vendors to offer specialized platforms, but the downside is that they can be out of reach of small organizations. But there’s a silver lining. Many vendors offer customized solutions, so we advise reaching out to the vendor for quotes.

    Users appreciate its regular updates, but some report initial bugs due to its relative newness. Despite a positive user experience, the learning curve can be steep. Some users found technical support slow and inadequate, as did I. They took two business days to get back to me when I needed assistance with my account.

    Oracle Analytics, though a robust platform, is suitable for mid- and large organizations. If you seek a powerful, scalable platform, consider opting for a trial, but be prepared for sticker shock, especially if you’re new to the Oracle ecosystem.

    Pros & Cons

    • User-Friendly: Citing its interface, about 91% of users agreed that a drag-and-drop UI makes it easy to use.
    • Machine Learning: Around 86% of users who discussed augmented analytics were impressed with its ML capabilities.
    • Integrations: Approximately 84% of users who mentioned connectivity said the platform worked well with other systems, especially Oracle products.
    • Functionality: According to 83% of users who reviewed capabilities, it has all the required features to support data tasks.
    • Data Visualization: Around 73% of users who mentioned visualization praised the platform for its storytelling features.
    • Price: About 88% of reviews citing pricing said that it’s too expensive.
    • Adoption: Approximately 87% of users who discussed onboarding said there’s a significant learning curve.

    Key Features

    • Deployment: Install and run anywhere, including as a hybrid solution. Scale the instance depending on your workload — deploy OCPUs in multiples of two, extending up to 52. Or pause it when idle. Though identity management is available, there is the option to use one’s own SSO provider. Admins can set user, group and role-based permissions.
    • Connectivity: Make decisions based on data; connect to social media feeds, data lakes and IoT sources. Store and process data at scale, irrespective of its volume, velocity and variety. Get started as soon as you log in with over 40 readymade connectors.
    • Direct Query: Oracle Analytics Cloud uses live queries and data caching to fetch responses. Each has its downside. Live connections are heavier on the system, and you might have to compromise on data freshness with data caching. A combination of both might be best. Consider live queries for critical KPIs and data caching for less frequent queries.
    • Data Preparation: Enrich data from the interface — get data quality insights as you work. Remove the grunt work — create reusable flows for transforming data you can test, share and schedule. Add custom calculations or write regular expressions in the dataset editor.
    • Semantic Data Modeling: Engage business, dev and data teams in meaningful discussions. Give them data views with a presentation layer that simplifies metrics. Hide the physical data structure with a logical one that speaks the business language. Give stakeholders the power to explore data independently.
    • AI/ML: Boost productivity with embedded machine learning and natural language insights every step of the way. Display quick forecasts, trend lines and clusters from a popup menu with one click. View the basic facts, key drivers and anomalies with the Explain option. Hit the ground running with recommendations on dimensions, measures and attributes to use when you don’t know where to start.
    • Oracle Analytics Publisher: Generate reports from any dataset or semantic model. Create formatted documents unique to your business, be it shipping labels, checks, letters or PDF forms.
    • Data Visualizations: Put your best foot forward with suitable charts and graphs that convey your message effectively. Modify them to answer users’ questions better. Choose from over 45 visualization types, or build your own using extensions from its vast library.
    • Embedded AI On Mobile: Get real-time alerts and intelligent recommendations on mobile. The Oracle Analytics mobile app captures your preferences and location. Upload datasets just like on the desktop or create a workbook from existing data. Powerful searches enable access to your favorite worksheets; add them to your home screen for a quick view. Use voice-enabled searches and listen to the results as a podcast.

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    All OLAP Tools (168 found)

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    Tableau

    by Tableau Software
    Tableau
    Tableau is a data visualization and analytics solution for enterprises and individuals. A rich library of connectors helps you pull data from files, cloud sources and servers. A separate data management module, Tableau Prep, ensures your data is ready to transform when it comes into the platform.Its latest features include AI with Tableau Pulse and the Einstein CoPilot.Software, healthcare, manufacturing, banking and financial services, and retail companies will find it helpful. Whatever your domain, chart, plot and map data will give you a clear picture of business performance.Besides, you can track daily operations and support line-of-business decisions with hardcore data. At the higher level, it boosts planning by giving senior management the freedom to dig deeper.A Tableau Creator license costs $70 per user and includes Tableau Desktop and Tableau Cloud. Alternatively, you can deploy it on-premise and connect to the cloud using a bridge. A free trial of Tableau Desktop is available, and Tableau Public is always free to use.Though it's a user favorite for data visualization, many users find it expensive and slow when handling large datasets.
    User Sentiment User satisfaction level icon: great
    Cost Breakdown
    $10 - $100
    Company Size
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    Power BI

    by Microsoft Corporation
    Power BI
    Microsoft Power BI is an analytics and reporting solution for individuals and enterprises. Ranked among the top five products in our BI product directory, it’s a user favorite, with 88% of reviewers giving it the thumbs up.It’s versatile in connectivity, pulling data from files, databases and cloud sources. Power Query helps users transform data to the desired format for building accurate models. They will serve as the basis for analysis and reporting. With Azure Machine Learning, Power BI incorporates AI into the analysis.Government agencies find them handy for tracking citizen programs, crime and health data, and utilities. For healthcare companies, it proves helpful in patient data tracking, population health management and operations. Retail is all about sales and revenue, and if this is you, the vendor offers ready-made report templates that can help you hit the ground running. That’s not all; other report samples are available too.Reusable dataflows in Power BI help you create a process once and run it again. Dataflows are shareable, so your whole team benefits. DAX enables complex calculations, while natural language Q A speeds up analysis. Team workspaces enable collaboration, and mobile insight is available.Individual accounts include Power BI Desktop, Power BI Pro and Premium per User (PPU). Pro and PPU licenses use Power BI Service, which lets you share content with other Pro users and is suitable for small businesses.Power BI Premium is an enterprise license; you can share content with anyone, even external users. Pro and PPU cost $9.99 and $20 per user monthly, while Premium comes at $4,995 per month. User reviews praise it for ease of use, connectivity and modeling, but most users find the pricing confusing, possibly because of the various Microsoft integrations that make Power BI a complete package.
    User Sentiment User satisfaction level icon: great
    Cost Breakdown
    $10 or less
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    Mathematica

    by Wolfram
    Mathematica
    Wolfram Mathematica is a technical computing platform that can perform a wide range of computations and algorithms for mathematics and beyond. Primarily designed for research and academia, it enables users to create powerful scripts through a flexible, multi-purpose programming language. It allows users to analyze and visualize data in sophisticated ways and employ methods such as machine learning, data mining and deep learning to model and solve complicated problems. It is available in the cloud through any web browser or installable on-premises on all desktop environments. Users can purchase licenses as individuals or under group or enterprise pricing for cloud, desktop or both versions.
    User Sentiment User satisfaction level icon: excellent
    Cost Breakdown
    $1,000 or more
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    Looker

    by Looker Data Sciences
    Looker
    Looker is a web-based analytics solution that offers businesses the ability to explore, discover, visualize and share data insights. Enterprises can view data sources and drill down into data to better understand their business and metrics. Using a simple proprietary modeling language, this system helps define data relationships while bypassing SQL. It facilitates data literacy and accessibility, irrespective of technical skill levels. It was acquired by Google on June 6, 2019, for $2.9 billion.
    User Sentiment User satisfaction level icon: great
    Cost Breakdown
    $1,000 or more
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    Qlik Sense

    by QLIK TECHNOLOGIES INC.
    Qlik Sense
    Qlik Sense is a self-service analytics solution that supports enterprise decisions and strategy. Its value lies in interactive dashboards and reports for exploring data independently. Embedded analytics lets your users work freely with data within their applications and websites.Like QlikView, Qlik Sense has an associative engine. It links data tables in memory, keeping the information ready for when your users build models. Plus, its cognitive engine uses natural language for data tasks.The Enterprise subscription includes Talend Data Integration and Qlik Advanced Analytics in Qlik Cloud. You can also choose Qlik Data Integration. Qlik Sense Enterprise SaaS includes 5000 automations and 100 reports. It might be a good fit if your data loads are predictable and don't change much. The vendor charges for the data you move or the volumes you analyze; you can choose between the two.Qlik Sense deploys on Windows, Mac, Linux and any phone device. By contrast, Tableau runs on Windows, Mac and mobile, while Power BI is available only on Windows and Android devices.Individual users can choose the desktop edition, though they’ll need a Qlik Cloud account to download it. A 30-day trial period is available, after which it'll cost $30 per user monthly.
    User Sentiment User satisfaction level icon: great
    Cost Breakdown
    $10 - $100
    Company Size
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    Mac Windows Linux Chromebook Android
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    Spark

    by Apache Software Foundation
    Spark
    Apache Spark is an open source unified analytics software for distributed, rapid processing. It distributes data across clusters in real time to produce market-leading speeds. It is rising in popularity in the space, catching up to its sister-offering, Hadoop, because of its quicker speeds and specific focus on optimizing processing performance and ability to stream data. It supports several coding languages, including Python, R, Scala, SQL and Java. It can function stand-alone, or be integrated into broader workflows easily.
    User Sentiment User satisfaction level icon: great
    Cost Breakdown
    $100 - $500
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    Mac Windows Linux Chromebook Android
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    Funnel

    by Datainspektionen
    Funnel
    Integrate data from different platforms with the aid of connectors to facilitate robust analysis. Access real-time data to extract useful insights. Export data to multiple destinations for advanced analysis and visualization. Consolidating data at a centralized location ensures users gauge ROI across different marketing channels and campaigns. Understand KPIs with up-to-date dashboards and reports. Leverage standard rules to define naming conventions for dimensions and metrics.
    User Sentiment User satisfaction level icon: excellent
    Cost Breakdown
    $100 - $500
    Company Size
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    Deployment
    Cloud On-Premise
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    Mac Windows Linux Chromebook Android
    Request with no obligation:
    Demo Pricing

    QlikView

    by QLIK TECHNOLOGIES INC.
    QlikView
    QlikView is a data discovery and customer insight platform from Qlik, a leader in the insight and intelligence space. However, it is not available for purchase any longer. Qlik Sense, Qlik’s next-generation offering, is available for new customers. It offers self-service data that can help drive decisions and generate significant ROI for technical skill level users. It’s built from the ground up to be affordable, scalable and adaptable. It can ingest data from diverse sources like big data streams, file-based data, and on-premise or cloud data. It is well-known for its data associations and relationship functionality, keeping data in context automatically. It delivers results quickly via its patented in-memory data processing module, processing data down to as little as 10% of its original size. Pros Intuitive interface Fast data visualization Easy data exploration User-friendly for non-technical users Strong community and support Cons Limited data modeling capabilities Licensing costs can be high Customization can be challenging Version control can be a concern Performance can slow with large datasets
    User Sentiment User satisfaction level icon: great
    Cost Breakdown
    $1,000 or more
    Company Size
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    Mac Windows Linux Chromebook Android
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    Spotfire

    by TIBCO Software Inc.
    Spotfire
    Spotfire is a software solution for business reporting and analytics. Ranked third on our product directory, it shines for data science and streaming analytics. Dashboards are customizable and interactive. Automation services help create and deliver reports on schedule. You can download it on Windows and access it through other operating systems via workarounds.Organizations across the board find Spotfire helpful, be it pharma companies or oil and gas suppliers. Manufacturing and supply chain businesses also opt for it on account of its functions and formulas. Techniques like regression and what-if analysis support predictions. Reporting on inventory levels can help you anticipate and plan when to place the next order.With a data tool, you expect to have data management built in, and Spotfire does an excellent job. It enables cleaning data from the user interface — inline data cleansing — and flags anomalies.Geomapping is sometimes an afterthought in BI tools. Spotfire scores with excellent location analytics and companies with field machinery find it helpful. Plan maintenance by keeping tabs on machine performance and aging trends using Spotfire dashboards.Spotfire has data management with anomaly detection and inline data cleansing. Geomapping is sometimes an afterthought in BI tools. Spotfire scores with excellent location analytics, which is why many companies with field machinery find it helpful.Spotfire's robust calculations are due to TIBCO's runtime engine. Report templates are available, and you can create your own. Its Automation Services help manage routine reporting.Users praise Spotfire for its connections with an active community that contributes additional connectors. They appreciate its visualizations and the freedom to customize data displays. The vendor provides exceptional support for mobile insights.The latest edition, Spotfire X, has NLQ-powered searches, AI recommendations and model-based processing. A 30-day trial with 250 GB of storage is available. At $1,250 per year, a Spotfire Analyst license costs more than Tableau and Power BI, and users agree that pricing is steep.
    User Sentiment User satisfaction level icon: great
    Cost Breakdown
    $10 or less
    Company Size
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    Oracle Analytics Cloud

    by Oracle America
    Oracle Analytics Cloud
    Oracle Analytics Cloud is a public cloud service on which you can build and run reporting and analytics solutions. It can also manage data from Oracle Database and Oracle Autonomous Data Warehouse. Pairing it with Oracle Data Integration can help you move and transform data at scale. But that’s not all. You can build and deploy analytics applications even with non-Oracle systems. However, the level of integration and capabilities may differ.You’ll need an Oracle Cloud account, and a free trial is available. Oracle customizes the view for you, whether you’re a web app developer, account admin or cloud architect. Workbooks and dashboards enable data exploration. You can set it up so the system sends reports to selected users on schedule. Governed analytics is available; your data stays secure. Annotations, export options and integration with social platforms are other capabilities.Two pricing tiers are available. The Professional edition has self-serve analytics, direct source connections and dataflows for preparing content. It costs $16 per user monthly.The Enterprise edition lets you enrich data, connect to private sources and build semantic models. You can track usage and set encryption keys, all at a cost of $80 per user monthly. Opt for a user or consumption model based on OCPUs (Oracle CPUs).The user reviews were an interesting read. I haven’t seen many products with such strongly divided opinions. In all positive reviews, over 70% of the users voted for a specific feature, indicating a high level of user satisfaction and perceived value. On the flip side, over 87% of users said price and a steep learning curve were blockers to successful adoption.
    User Sentiment User satisfaction level icon: great
    Cost Breakdown
    $10 - $100
    Company Size
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    Sisense

    by Sisense
    Sisense
    Sisense is an end-to-end data analytics platform that makes data discovery and analytics accessible to customers and employees alike via an embeddable, scalable architecture. With a back-end powered by in-chip technology, it allows analysts to blend large datasets from a variety of sources into a single cohesive database for the entire company. On the front-end, users of all technical skill levels can craft visualizations, reports and dashboards to explore and share insights that drive businesses forward. Its AI-driven, cloud-native analytics offering, Fusion, embeds into business workspaces and empowers teams to view key metrics and data insights where they work. Designed for companies of all sizes, it can be deployed on-premises, as a private cloud-hosted SaaS, as a fully managed SaaS or via a hybrid strategy. It is available via annual subscription pricing and offered in three packages: its main offering BI Analytics Teams, its embedded analytics component Product Teams and code-driven cloud analytics through Cloud Data Teams.
    User Sentiment User satisfaction level icon: great
    Cost Breakdown
    $1,000 or more
    Company Size
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    Deployment
    Cloud On-Premise
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    Mac Windows Linux Chromebook Android
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    Cognos Analytics

    by IBM
    Cognos Analytics
    IBM Cognos Analytics is a self-service, web-based analytics platform which empowers users of all skill levels to explore data through reporting, data analytics, KPI monitoring, events and metrics. Reports give users the ability to not just visualize their insights, but also share them with colleagues. It integrates with Watson Analytics, which leverages IBM’s artificial intelligence and natural language processing to make insights more accessible to non-technical users. It has various components which give additional functionality, flexibility and agility when processing large sets of data.
    User Sentiment User satisfaction level icon: great
    Cost Breakdown
    $10 - $100
    Company Size
    Small Medium Large
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    Mac Windows Linux Chromebook Android
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    Minitab

    by Minitab
    Minitab
    Minitab is a statistics package that delivers statistical analysis, data visualizations and data analytics to help users improve data-driven decision making by streamlining their analytical workflow. It can analyze all kinds of datasets, from small to large, and automates statistical calculations and the creation of graphs, allowing users to focus more on data analysis. It enables users a range of customization options and has powerful scripting macro capabilities.It is currently available for on-premise installation on Windows or Mac operating systems only, with no SaaS or mobile options. Customers may choose between a single license for a stand-alone copy or an annual network license for multiple users, which includes upgrades to new versions. The company offers government and academic pricing options as well.
    User Sentiment User satisfaction level icon: excellent
    Cost Breakdown
    $500 - $1,000
    Company Size
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    Mac Windows Linux Chromebook Android
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    BusinessObjects

    by SAP, Inc.
    BusinessObjects
    BusinessObjects is a suite of business intelligence (BI) tools that helps organizations collect, analyze, and visualize data to make better decisions. It's most suited for large enterprises with complex data needs, as it offers a wide range of features and capabilities. Key benefits include improved data visibility, enhanced decision-making, and increased productivity. Popular features include data modeling, reporting, ad hoc querying, and dashboards. User experiences highlight its ease of use, robust functionality, and scalability, though some note its potential for complexity and higher learning curve. Compared to similar products, BusinessObjects often stands out for its comprehensiveness and integration capabilities. Pricing is typically based on a per-user or per-named-user basis, with annual subscription fees. Pros Easy to use Robust features Scalable Comprehensive Integrates well Cons Can be complex Steeper learning curve Costly May require training Can be resource-intensive
    User Sentiment User satisfaction level icon: great
    Cost Breakdown
    $1,000 or more
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    MicroStrategy

    by MicroStrategy
    MicroStrategy
    MicroStrategy is a data visualization and reporting platform that deploys on-premise and on the web. The cloud version runs on AWS or Microsoft Azure. MicroStrategy Library is the web edition, while Workstation is the desktop version.It reigns supreme as the top analytics tool in our product directory and provides 91% of the required features out of the box. Regarding source data integration, it leaves very little to chance, winning our best-in-class award for connectivity. With over 200 connectors, there’s a high chance it’ll satisfy your data needs.If not, you can build one using a software development kit. SDKs are also the force behind REST and embedding APIs, HyperIntelligence and data visualization. Plus, the semantic layer enables automating data prep and analysis and generating visualizations on cue.Dossiers in MicroStrategy are like books; they have chapters further divided into pages, and each page has one or more visualizations. Every view is free-form — you can move charts around and organize them as you like. With write-back capability, you can update underlying databases from visualizations.The vendor launched its unified cloud AI analytics platform, MicroStrategy One, with GPT-4o in September 2024. It’s twice as fast, digging into the selected data to produce dashboard summaries and answer user queries in seconds. Update 12 has auditing capabilities and shows details of active licenses, including their compliance status.Its heart and soul is an Intelligence Server that manages metadata and processes queries. A mobile app is available. There’s a 30-day trial, but access to group permissions, KPIs and subscriptions requires a paid upgrade.User reviews mentioned that the solution was effective, but the ecosystem and pricing were complex.
    User Sentiment User satisfaction level icon: great
    Cost Breakdown
    $10 - $100
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    Sisense For Cloud Data Teams

    by Periscope Data
    Sisense For Cloud Data Teams
    Formerly known as Periscope Data, Sisense for Cloud Data Teams is a data analytics software tool that integrates seamlessly with the Sisense platform, offering advanced analytics that delivers actionable insights to teams that work with data in the cloud. It provides a single, cohesive interface for users to store, organize, analyze and visualize all their data for better decision-making. It empowers users of all kinds to produce, consume and share insights intuitively together, with or without coding knowledge. Originally founded in 2012 in San Francisco, California, it was acquired by Sisense in May 2019 and rebranded in January 2020.
    User Sentiment User satisfaction level icon: great
    Cost Breakdown
    $100 - $500
    Company Size
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    Deployment
    Cloud On-Premise
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    Mac Windows Linux Chromebook Android
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    ThoughtSpot

    by ThoughtSpot
    ThoughtSpot
    ThoughtSpot is a cloud-based business intelligence and analytics platform that empowers users of all skill levels to explore and analyze data through a search-driven interface. It leverages artificial intelligence and natural language processing to simplify data analysis, making it accessible to a wider audience. ThoughtSpot is particularly well-suited for organizations seeking to democratize data access and promote data-driven decision-making across various departments. Key benefits include ease of use, accessibility from any device, and the ability to connect to diverse data sources for real-time insights. Popular features encompass interactive dashboards, AI-powered insights, and natural language search capabilities. In comparison to similar business intelligence tools, ThoughtSpot stands out for its user-friendly interface and emphasis on search-driven analytics. While some users find its pricing to be on the higher end of the spectrum, many appreciate the platform's ease of use and the value it delivers in terms of improved decision-making and operational efficiency. ThoughtSpot's pricing structure typically involves annual subscriptions based on the number of users and data volume.
    User Sentiment User satisfaction level icon: great
    Cost Breakdown
    $10 - $100
    Company Size
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    Deployment
    Cloud On-Premise
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    Mac Windows Linux Chromebook Android
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    Pentaho

    by Hitachi Vantara
    Pentaho
    Pentaho is a data integration and analytics platform that helps businesses extract, transform, analyze, and visualize data from diverse sources. It caters to organizations navigating growing data volumes and seeking insights for informed decision-making. Users praise Pentaho's open-source, free core version, making it a budget-friendly option for beginners or small teams. Its wide range of tools tackles various data challenges, from basic reporting to advanced analytics. Scalability shines for larger datasets, handling complex processing effectively. Additionally, an active community offers valuable support. However, prepare for a steeper learning curve compared to more user-friendly options. Limited documentation can occasionally leave users struggling. Users report encountering bugs and glitches, potentially requiring technical expertise. Be mindful of resource intensiveness, as large-scale operations might demand powerful hardware. While customization options exist, some users crave more flexibility. Overall, Pentaho offers a powerful, free data platform, with trade-offs between its extensive capabilities and ease of use. Consider its strengths and limitations in the context of your specific needs and technical expertise. Pros Open-source and free Wide range of tools Scalable for large datasets Active community support Integration with various platforms Cons Steeper learning curve Limited documentation Occasional bugs and glitches Can be resource-intensive Limited customization options
    User Sentiment User satisfaction level icon: great
    Cost Breakdown
    $10 - $100
    Company Size
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    Deployment
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    Mac Windows Linux Chromebook Android
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    Klipfolio

    by Klipfolio Inc.
    Klipfolio
    Klipfolio is an analytics software tool that helps users wield data intelligently and confidently by building dashboards and reports that track KPIs and monitor trends. Users can glean insights from information across the organization collected in one convenient place and deploy interactive data visualizations that they can share with ease. It is available through an annual or monthly subscription to one of four plans: Publish, Grow, Team and Team+. The number of dashboards and users allowed, as well as the data refresh rate and level of support varies depending on the pricing plan selected.
    User Sentiment User satisfaction level icon: excellent
    Cost Breakdown
    $1,000 or more
    Company Size
    Small Medium Large
    Deployment
    Cloud On-Premise
    Platform
    Mac Windows Linux Chromebook Android
    Request with no obligation:
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    RStudio

    by RStudio
    RStudio
    RStudio is an integrated development environment suite for the R programming language, synthesizing coding tools into one software tool for easier advanced data processing. Using in-memory processing, it is capable of parsing big data through integrations and connections. It is available in both open-source and commercial formats, with extra features available in the paid edition includes more sophisticated collaboration and security efforts. The free version is capable of end-to-end analytics, from API connectivity and data ingestion to visualization creation and distribution. It can be deployed standalone or on a web browser through connection to RStudio Server.
    User Sentiment User satisfaction level icon: excellent
    Cost Breakdown
    $1,000 or more
    Company Size
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    Deployment
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    Buyer's Guide

    OLAP Tools Are All About Gaining New Data Views 

    By Ritinder Kaur, Market Analyst at SelectHub

    OLAP Tools BG Intro

    OLAP is a computing approach to multidimensional data analysis. OLAP tools are in demand as companies seek to delve deeper into multidimensional metrics without compromising performance. Many are analytics and BI tools with OLAP engines embedded into them.

    Whether you plan to buy a new software solution or add an OLAP engine to your existing one, this buyer’s guide will take you through the steps necessary to choose one that fits. It informs you how to evaluate and compare OLAP systems based on their features and functionality. Additionally, we give you handy tips and resources to aid your software search.

    Executive Summary

    • OLAP tools enable drilling into multidimensional business metrics to reveal performance insight, including previously unknown patterns.
    • OLAP cubes improve query performance by reducing computing overheads on warehouses through in-memory processing.
    • MOLAP and ROLAP are the most common OLAP servers in use.
    • Read about the most popular OLAP tools in the market to know which features to add to your requirements checklist.
    • Spell out your business needs clearly by preparing questions before approaching vendors.
    What This Guide Covers:

    What Are OLAP Tools?

    OLAP platforms are software solutions for the interactive analysis of multidimensional information stored in databases and data warehouses. OLAP supports faster ad hoc queries and complex analytical calculations for business intelligence, reporting, predictive analytics and decision support.

    While OLAP focuses on analysis, online transaction processing (OLTP) involves executing transactions concurrently in real time, like online banking, order processing, payment workflows and sending messages.

    OLTP use cases include eCommerce software, credit card payment processing, record-keeping tools, ATMs and online booking and reservation systems. OLAP enables business reporting for sales, marketing, employee performance management (EPM), budgeting and forecasting, including financial reporting.

    Traditional querying methods fall short in the case of multidimensional metrics, as increasing volumes can slow down performance. Additionally, reorganizing the results to highlight different dimensions is resource-draining.

    OLAP databases use a multidimensional model for storing information and support complex ad hoc and analytics queries with a fast runtime. OLAP systems are mostly read-only to keep computing time to a minimum.

    The OLAP cube is at the center of an OLAP system and abstracts multidimensional data analysis from warehouses and databases through in-memory computing.

    OLAP Tools Categories

    Cubes, Dimensions, Measures

    An OLAP cube is to OLAP what a schema is to relational data. It’s a multidimensional format created by reorganizing information from multiple relational data sets.

    The actual values or facts you analyze, like product quantity and sales figures, are called measures. Dimensions are the various views for a measure in an OLAP cube, for instance, employee, date, customer, product and area fields for the same sales numbers.

    Metadata is an essential component of the OLAP cube and contains key information about measure groups and their relationship to dimensions with their storage details. It includes another business-critical element — Multidimensional Expressions (MDX) scripts to add code for data processing. Additionally, you can define user actions to open and view reports and drill into the metrics for a closer look.

    OLAP helps you analyze your data through consolidation, drill-down and pivoting.

    OLAP Operations

    These tools perform four basic operations:

    1. Drill-down involves moving down the dimension hierarchy in the OLAP cube. For instance, you could expand the sales figures for a region to view the numbers for individual products.
    2. Consolidation (Roll-up) is the reverse of drill-down and involves gaining a high-level overview by moving up the hierarchy or reducing the number of dimensions. To view the overall projections, you can aggregate individual store data and show it against the consolidated sales dimension.
    3. Slicing involves isolating a single dimension from the central OLAP cube. Viewing the revenue numbers for the last six months is an example of slicing the year (time dimension).
    4. Dicing involves drilling down into more than one dimension simultaneously. You can dice years (time dimension) into months and countries (location dimension) into cities simultaneously, creating smaller cubes from the central OLAP cube.
    5. The pivot feature is similar to the pivot table feature in MS Excel. Fast OLAP querying enables rotating the cube view for disparate data views.

    MOLAP, ROLAP and HOLAP

    These are terminologies associated with data warehouses representing logical data models.

    • Multidimensional OLAP or MOLAP is the concept of directly processing data in OLAP cubes.
    • Relational OLAP or ROLAP involves analyzing multidimensional data from relational tables in warehouses. But, performance issues due to complex queries can slow down processing. Additionally, data views in ROLAP are static, making pivoting impossible.
    • The hybrid OLAP (HOLAP) approach provides the benefits of ROLAP and MOLAP — access to larger information volumes and fast processing. But, performance issues can slow down your analytics pipeline due to its complex architecture.

    Primary Benefits

    OLAP answers questions standard tables can’t solve, driving rapid analysis and proactive action to help complete projects on time.

    OLAP Tools Primary Benefits

    Reduce Time to Market

    OLAP systems speed up product development and delivery cycles, helping establish your brand’s market reputation as a serious player. OLAP engines save time by pre-aggregating variables and conducting lightning-speed business calculations. Near real-time insight gives relevant results, giving you a chance to take timely action.

    Sharable data cubes save time by promoting collaboration. Additionally, they boost warehouse performance by eliminating the burden of repeated queries.

    Gain Data Insight

    God is indeed in the details, and so is valuable business insight. Roll-up, slice-and-dice and pivot actions help zoom in and out of granular views in OLAP cubes, revealing correlations you didn’t know existed.

    Uncovering data relationships can reveal previously unknown market trends, gaps and opportunities.

    For instance, you can slice the location dimension into states, regions and cities for detailed views of performance metrics. Drilling down helps highlight gaps not apparent otherwise and successes you didn’t notice in the high-level view.

    Build Comprehensive Reports

    Many OLAP tools provide interactive visualizations for ad hoc analysis and reporting. With quick data access, manipulating datasets directly within the data cubes speeds up the analytics process. Despite being fast, OLAP servers perform accurate calculations, ensuring the correct information feeds your reports.

    You can build predictive models by moving the datasets around for what-if analysis. Configuring individual permissions at the report level ensures your users see only the pertinent metrics.

    Democratize Data

    Modern OLAP tools have an intuitive interface with easy user actions to perform analysis without technical assistance. You can analyze data independently by connecting to the desired sources and interacting with the datasets to show the necessary metrics.

    Select-and-click and drag-and-drop actions help you perform complex calculations across multiple dimensions — all the SQL querying happens at the backend. You can calculate the revenue earned from stores in Florida as a percentage of the total revenue for the current year and view its progression in a time-series analysis.

    OLAP cubes are scalable, limiting data consumption by incorporating only the required datasets.

    Key Features & Functionality

    Ease of use, accessibility and support for complex calculations and standard dimensions are business-critical features in an OLAP software solution.

    Transparency

    The OLAP tool should provide complete transparency into your homogeneous and heterogeneous information sources. Full visibility into the OLAP computing architecture and the underlying databases is essential for monitoring and troubleshooting.
    Accessibility

    OLAP servers seamlessly connect to client systems and source databases.

    An OLAP tool presents a single source of truth by mapping its logical schema to available data stores, aggregating the information and performing the necessary transformations.

    Consistent performance is business-critical, irrespective of the increase in the number of dimensions or the database size.
    Intuitive Data Manipulation

    OLAP operations — drill-down, pivot and slice-and-dice — enable a deep-dive analysis of multidimensional information. Intuitive user actions like select-and-click and drag-and-drop are essential to ensure quick turnaround and proactive decision-making.
    Complex Calculations

    Calculations help you extend the cube’s capabilities, flexibility and robustness in business intelligence applications.

    A calculation is an MDX expression or script used to define a value at run time in a cube. Calculations let you add objects the cube data doesn’t define, and they can reference other parts of the cube, other cubes or values outside the underlying database.

    The OLAP system should provide powerful calculation methods for sales forecasting, such as moving averages and percentage growth.
    Location and Time Intelligence

    Location and time are standard dimensions for OLAP analysis. Period-over-period comparisons enable reviewing past performance and planning business strategy using what-if scenarios.

    Software Comparison Strategy

    Our lean selection methodology breaks down the process for you, whether you plan to buy a new software solution or add an OLAP module to your existing one.

    Create a requirements checklist to assess your internal organizational needs. We can help you hit the ground running with our pre-populated, customizable requirements template.

    Finalize and freeze your key requirements in consultation with top management and other stakeholders, including teams that will use the software. Convert the requirements into questions and distribute them to potential vendors with a request for proposal (RFP).

    Review vendor proposals and rank the products on a scale of 1 to 100, depending on how well they address your business needs. Refer to our Jumpstart platform for access to comparative analysis and scores of leading OLAP tools based on our analyst research.

    Cost & Pricing Considerations

    Budget constraints can weigh you down when seeking new software solutions or upgrades. It’s best to check the pricing tiers from the vendor’s website or contact them directly. Refer to our pricing guide to learn how much an OLAP solution will likely cost you.

    Pricing will vary across products, depending on the deployment option, user licenses and additional modules you choose. Often, the product package includes basic support, though you must opt for a paid plan for personalized assistance. Attention to these details can help you put a number to the total cost of ownership (TCO).

    The Most Popular OLAP Tools

    We conducted an in-depth analysis of the leading OLAP tools based on how well they deliver enterprise requirements. Here are the three most popular products.

    Power BI

    Microsoft supports MDX and Data Analysis Expressions (DAX) with live connections to Microsoft SQL Server Analysis Services (SSAS) models. Most Power BI visuals benefit from improved query performance using SuperDAX —- enhancements for consolidating multiple operations within a standard DAX query. Microsoft’s latest innovation is Horizontal Fusion, combining smaller queries into a larger one to reduce processing demands.

    Power BI

    Horizontal Fusion in Power BI improves query speed and scalability.

    Oracle Analytics Cloud (OAC)

    Oracle OLAP is an analytic engine embedded in Oracle Database 12c, enabling centralized management of business information and rules in a scalable, secure platform. It’s a robust enterprise solution, allowing you to create custom functions by combining hundreds of analytics functions. Lightning-speed SQL queries let you deploy OLAP cubes as materialized views.

    Oracle Analytics Cloud

    Defining a materialized view in OAC.

    MicroStrategy

    MicroStrategy’s versions 9.0 and later support Intelligent Cubes, which the system generates automatically on running new reports against the data warehouse. The platform’s logic automatically matches user requests with a suitable intelligent cube without manual intervention.

    MicroStrategy incorporates third-party data mining and modeling tools for predictive analysis.

    MicroStrategy

    Multidimensional data analysis and reporting in MicroStrategy.

     

     

    Questions To Ask

    Pose questions to team members and senior stakeholders to understand your teams’ expectations. You can fine tune your requirements list by matching product features to your business needs.

    • What’s not working with the present system? Do your company’s needs extend beyond multidimensional data analysis?
    • Will add-on OLAP modules work, or will you need a standalone solution?
    • What’s your budget?
    • Is predictive modeling a deal-breaker?
    • Which analytics functions will you need for complex calculations?

    OLAP Tools Key Questions To Ask

    Meeting up with vendors is an excellent way to narrow down your shortlist. Preparing questions beforehand saves time and helps you clarify your requirements and expectations during vendor discussions.

    • Are the OLAP techniques easy to use?
    • Are self-service visualization and dashboard reporting available?
    • Does the vendor provide training?
    • How often do they release updates and patch fixes?
    • What is the average support response time?

    In Conclusion

    Software selection demands due diligence and extensive research and can be time-consuming. It’s natural to feel frustrated at the slow pace as you sift through seemingly overwhelming information about the various OLAP tools in the market. But it’s worth it.

    Staying tuned to your business needs while defining requirements, matching product features and holding vendor discussions can help you make the right choice.

    Once you shortlist eligible vendors, contact the top one for final discussions, else move down the list. If all goes well, finalize the purchase and set up a deployment plan with clear timelines on when to go live.

    Reach out to our Managed Services team to assist you through the process.

    Product Comparisons

    About The Contributors

    The following expert team members are responsible for creating, reviewing, and fact checking the accuracy of this content.

    Ritinder
    By Ritinder Kaur
    Technical Content Writer
    Ritinder Kaur is a Senior Technical Content Writer at SelectHub and has eight years of experience writing about B2B software and quality assurance. She has a Masters degree in English language and literature and writes about Business Intelligence and Data Science. Her articles on software testing have been published on Stickyminds.
    See Full Bio
    Sagardeep
    Technical Research By Sagardeep Roy
    Senior Analyst
    Sagardeep is a Senior Research Analyst at SelectHub, specializing in diverse technical categories. His expertise spans Business Intelligence, Analytics, Big Data, ETL, Cybersecurity, artificial intelligence and machine learning, with additional proficiency in EHR and Medical Billing. Holding a Master of Technology in Data Science from Amity University, Noida, and a Bachelor of Technology in Computer Science from West Bengal University of Technology, his experience across technology, healthcare, and market research extends back to 2016. As a certified Data Science and Business Analytics professional, he approaches complex projects with a results-oriented mindset, prioritizing individual excellence and collaborative success.
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    Manan
    Technical Review By Manan Roy
    Principal Analyst
    Manan is a native of Tezpur, Assam (India), who currently lives in Kolkata, West Bengal (India). At SelectHub, he works on categories like CRM, HR, PPM, BI, and EHR. He has a Bachelor of Technology in CSE from The Gandhi Institute of Engineering and Technology, a Master of Technology from The Institute of Engineering and Management IT, and an MBA in Finance from St. Xavier's College. He's published two research papers, one in a conference and the other in a journal, during his Master of Technology.
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    Hunter
    Edited By Hunter Lowe
    Content Editor
    Hunter Lowe is a Content Editor, Writer and Market Analyst at SelectHub. His team covers categories that range from ERP and business intelligence to transportation and supply chain management. Hunter is an avid reader and Dungeons and Dragons addict who studied English and Creative Writing through college. In his free time, you'll likely find him devising new dungeons for his players to explore, checking out the latest video games, writing his next horror story or running around with his daughter.
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