As the name suggests, business intelligence involves making intelligent decisions using historical data to improve existing strategies and outperform the competition. Here’s our recommended list of eleven key features of business intelligence tools that will help any organization create a massive impact on their customers and provide a seamless experience.
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What This Guide Covers
Key Features
Some crucial features of business intelligence (BI) include:
1. Reporting
With an intuitive platform, you can create and distribute reports on the fly without IT assistance. Schedule reports automatically to ensure delivery at recurring times. Set built-in alerts to distribute reports when you meet specific conditions.
Leverage conditional formatting capabilities to highlight cells within reports when a particular condition is satisfied. Interactive reporting inclusions let you interact with different report views and filter, drill down, pivot, sort, resize rows and columns, add totals and more.
2. Advanced Analytics
Advanced analytics allows you to perform complex data manipulation and analysis. It facilitates regression analysis to analyze relationships between dependent and independent variables.
If you’re curious about how a future decision will affect your business, you can run a what-if analysis using past data to predict potential outcomes. What-if analysis tools give you an objective view of the risks and rewards involved in each decision.
Modern BI tools also support scenario analysis to compare potential outcomes based on dynamic parameters. Perform statistical analysis using advanced functions like mean, median, mode, standard deviation, kurtosis and more.
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3. Data Visualization
Beautiful and interactive data visualizations let you present complex information in simple formats. BI tools like Tableau and Power BI can create advanced and sophisticated visualizations that effectively convey data.
Create robust dashboards to analyze data trends.
Executive dashboards give your organization’s leaders a real-time overview of your business in the form of graphs, charts, summaries and other information reports. Visibility and accessible visualizations help executives make smarter, faster and better decisions.
Drill-up and drill-down capabilities allow you to explore multi-dimensional, hierarchical data. The other built-in functions such as scaling, sorting, filtering, tooltips and highlighting enable you to interact with the dashboards and unearth valuable insights.
4. Geospatial Analysis
Find locations on the fly in map view with geographic map search functionality. Applications using location intelligence can take your information and transform it into graphical and cartographic representations, simplifying your geographical data.
Find a suitable place to stay based on your needs.
At a glance, judging which regions are performing better than others — and which ones need particular attention — becomes much more manageable.
5. Mobile BI
Mobile business intelligence refers to accessing data and performing analysis on mobile devices and tablets. Mobile BI provides on-the-go access to KPIs, metrics and dashboards to make intelligent business decisions.
Add comments and share annotated mobile screens to facilitate collaboration between team members. It offers mobile-optimized dashboards and interactive reports.
6. Data Management
Data management involves preparing, blending, exploring and cleaning data for analysis. Combine multiple data sets to create a new one.
Explore data to uncover trends, patterns, characteristics and points of interest while describing them using visualization tools. Perform OLAP operations like drill-up, drill-down, and slice and dice to facilitate in-depth data analysis.
7. Self-Service Analytics
A robust BI platform should enable everyone in your organization to interact with data and derive meaningful insights regardless of their skills. Self-service analytics capabilities help you foster data culture by making information accessible to everyone.
The right BI solution establishes a secured and governed environment to protect data and ensure integrity without compromising agility and innovation.
8. Data Integration
The most powerful BI solution fails if it can’t connect to existing data sources. The right analytics platform provides optimized native connections to perform faster analysis, no matter where the data resides.
You can query the database quickly without writing custom code. It should seamlessly integrate with the existing data strategy without investing in additional products, thus disrupting your current data infrastructure.
It facilitates connections to various platforms, including ERP and CRM tools, eCommerce and big data solutions, cloud file storage systems and more.
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9. Predictive Analytics
You need to make accurate predictions to thrive in the dynamic business world. Predictive analytics leverages data mining, machine learning, statistics and artificial intelligence to analyze current and historical data to make accurate forecasts.
Make accurate forecasts based on historical data.
Business intelligence solutions can leverage predictive analytics to detect fraudulent transactions, inaccurate credit applications, identify theft and false insurance claims. They can also analyze customer buying behavior to gauge cross-selling and upselling opportunities.
10. User-Specific Security
Suppose you need to restrict certain users’ access to particular data sets. Your BI tool should allow you to personalize your BI features and applications to individuals or groups of users. Some solutions provide user-specific data sources, where a single application pulls data from different sources depending on who’s using it.
11. Augmented Analytics
Augmented analytics employs machine learning automation to improve data profiling and quality. Set alerts and notifications or display outliers/anomalies when data changes. Find new segments or clusters in the dataset automatically. Detect fundamental insights such as variances, correlations, trends and associations before exploring the data actively.
Use text- and voice-based searching to find relevant data using natural language statements.
Industry-Specific Benefits
Retail
The retail industry is a complex field that requires focus on several core aspects like supplier collaboration, supply chain management, merchandise disposition and analytics to ensure efficient operations.
Organizations within the retail sector opt for business intelligence tools to become more innovative, improve decision-making, and boost operational and financial performance.
Here’s how BI features benefit the retail industry:
OLAP: Retail industries gather multi-dimensional data from distinct, siloed sources. OLAP lets you view business data along various dimensions to gauge trends, patterns, characteristics and outliers.
It allows you to evaluate what if scenarios, estimate raw materials and project costs, prepare a detailed budget, optimize supply chains and ensure seamless operations.
Reporting: Create automated, timely reports to track KPIs and metrics. Receive time-bound insights about sales margins, analyze web-based sales compared to in-store purchases and analyze cost fluctuations, depleted resources, asset depreciation costs and more.
Data Mining: Leverage data mining techniques such as classification, clustering and regression to identify hidden patterns and relationships within datasets. With the aid of data mining algorithms, you can view patterns in terms of order placement, average customer journey times, client satisfaction ratio, marketing campaign efficiency and more.
Dashboards: Built-in dashboards can provide summarized information about the organization’s focal points. View critical performance data like CTR, conversions, customer retention rates, inventory turnover, year-over-year growth and more.
Healthcare
Healthcare organizations adopt clinical business intelligence tools to drive data-driven insights and boost patient care. Hospitals and clinics use business intelligence to store data in a centralized data warehouse to make it accessible to different departments while keeping it secure.
Let’s see how business intelligence features affect the healthcare industry:
Dashboards: You can monitor KPIs such as readmission rates, hospital infection rates and staffing shortages with robust dashboards that update in real time.
Predictive Analytics: Medical facilities can leverage predictive analytics to boost patient engagement and strengthen relationships with physicians. You can create patient profiles and send customized messages and recommendations based on patient history.
Leverage predictive algorithms to analyze patient data and develop dynamic customer personas to enable targeted marketing. For example, marketing personnel can curate email campaigns for personas that adhere to specific treatments.
Manufacturing
Business intelligence features can affect the manufacturing industry in the following ways:
Data Visualization and Dashboards: Intuitively present data and insights from machines, sensors and systems to monitor and optimize production quality. Robust dashboards offer complete visibility into production lines and provide insights on shop floor activities at a glance.
Forecasting: Create budgets that incorporate production, sales, operations, fulfillment and more. Determine resource requirements and create materials inventory beforehand to follow customer delivery commitments. Predict the idle capacity of machines to optimize production and boost efficiency.
Advanced Analytics: Leverage automation and artificial intelligence to mine data for patterns and insights. Monitor market trends and fluctuations and model risks and opportunities using neural networks and semantic analysis inclusions.
Key Survey Insights
- Advanced analytics features are not commonly considered as present requirements.
- Basic features are the most desired, with dashboarding being the most-mentioned feature.
- Most buyers do not have a deployment method preference.
Based on responses from representatives of over 600 businesses, we’ve compiled a list of the top features business intelligence software buyers are looking for. Our respondents represented a number of different industries, ranging from government entities and law firms to guitar retailers and aerospace electronic manufacturers.
Their answers provided us with data on the features most desired by those in the market for a business intelligence system.
Advanced Analytics Features Are Typically Viewed as Amenities, Not Necessities
Viewed as a more advanced feature, predictive analytics is still one of the top needs of BI software buyers, with 42% of respondents expressing interest in predictive analytics. Predictive analytics functions allow users to interpret data through the lens of patterns and trends, and use those findings to forecast future performance.
Of the buyers who named predictive analytics as a key feature, 16% considered predictive analytics as something that would be “nice to have in the future,” as opposed to a feature that would be needed upon deployment. It seems many buyers are interested in predictive analytics but may be unsure of how the feature can benefit their business currently.
The reluctance towards immediately investing in predictive analytics may also stem from unfamiliarity with business intelligence software and a desire to become acquainted with the basics before delving into more intricate functions.
Data mining, ETL, online analytical processing (OLAP) and drill-down functionality were also top advanced analytics features. Data mining, which involves the exploration and analysis of large data sets, was named as a key feature by 32% of survey respondents. ETL (a.k.a. the ability to Extract, Transform and Load data) was chosen by 20% of buyers as a needed feature of business intelligence software.
OLAP functionality was considered a key feature by 14% of survey respondents. Having the option to “drill down” into data, which involves delving into the details of a data set, is a feature that was mentioned in 10% of responses.
Similar to predictive analytics, these features were seen as bonuses that may be put in place in the future, or would be beneficial now but not necessary. Among the respondents who mentioned data mining, 14% identified the feature as a “nice to have”. ETL was considered “nice to have” by six percent of respondents with interest in the feature, and buyers said the same of OLAP in 12% of responses.
The consideration of data mining, ETL, OLAP and drill-down functionality as less popular features may, like predictive analytics, be due to lack of awareness or a need to begin the adoption of BI software with basic features.
However, there may not have been as much of a need for these features because of their association with large data sets. Data mining, ETL, OLAP and drill-down functionality are generally big data functions and may not be needed by small businesses, or the perception of these features could turn away small businesses.
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Basic Features are Most Desired
Of our survey respondents, 90% named dashboarding as a key feature when searching for business intelligence software. The need to view data visualizations and other important information in a centralized location was seen as crucial.
Common motivation behind purchasing BI software is often a need to process and organize data into an easily digestible format. Dashboards satisfy this need for simplified data presentation and are therefore a requirement by an overwhelming majority of buyers.
Visualizations stood out as another important feature for BI system buyers. The need to view data in an easy-to-understand medium is considered essential for most users of BI. Visualizations present data in a format that can be absorbed by people of all levels of BI skill sets. The feature was mentioned in 81% of responses.
The desire for a tool that can transform data from numbers on a spreadsheet to insightful visualizations is a common motivating factor for beginning the search for BI software, so the feature’s popularity is understandable.
The ability to create reports was another top response, considered a basic BI feature along with dashboards and visualizations.
Although reporting was not as popular as a response (48% of buyers reported a need for this feature), it is still considered a standard feature for business intelligence software. Collecting and preparing data is an important step to beginning deeper analysis.
Buyers’ Don’t Have a Deployment Preference
Deployment preferences of survey respondents were overwhelmingly on the fence, with 69% saying they were open to both methods of deployment. Of those respondents, 10% expressed a preference toward cloud-based deployment (although still undecided), and an equal number of buyers expressed a preference for on-premise deployment.
Buyers who firmly decided on a deployment method named the cloud as the favorable deployment choice, with 23% saying they would like a cloud-deployable system, compared to 8% demonstrating a want for on-premise deployment. Respondents cited cost, existing infrastructure, the volume of data and security (particularly government and HIPAA regulations) as factors under consideration when deciding on a deployment method.
The uncertainty found in deployment-focused responses could possibly be another awareness issue, as so many buyers did not favor either method and seemed unsure of the advantages one method has over the other.
The idea of adopting a “hybrid” model was mentioned in two percent of responses that expressed interest in both deployment methods, demonstrating buyers’ attraction toward the virtues of both.
Other Needs of Buyers
Some other key features of BI identified by survey respondents include data warehousing with five percent of buyers identifying a want for the feature, drag-and-drop functions at two percent and AI/machine learning at one percent. Many respondents wanted an embeddable system, with 23% expressing interest in the ability to integrate with programs such as Microsoft Office, Workday, Quickbooks, Salesforce, Hadoop and Google Analytics.
A desire for mobile capabilities, shareability and employee self-service were overarching themes as well. Four percent of buyers said they would like a mobile system. One percent expressed their need to share reports. The terms “self-service,” “user-friendly” or “ease of use” were found in 28% of responses.
Conclusion
Different organizations need different business intelligence features depending upon their requirements. It is best to invest in a solution that offers core features like dashboarding and visualization, reporting, data integration and more to start. Later, you can upgrade your solution to accommodate additional features, including predictive analytics, mobile business intelligence, augmented analytics and more.
What features of business intelligence do you use to boost business productivity and profitability? Let us know in the comments below!