Sisense For Cloud Data Teams vs ThoughtSpot

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Our analysts compared Sisense For Cloud Data Teams vs ThoughtSpot based on data from our 400+ point analysis of Business Intelligence Tools, user reviews and our own crowdsourced data from our free software selection platform.

Sisense For Cloud Data Teams Software Tool
ThoughtSpot Software Tool

Product Basics

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.
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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.

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Product Insights

  • Transforms Data Fast: Perform timely data querying and large-scale data ingestion for any volume of workload, through the analytics warehouse integration. Plug the data engine directly into cloud databases and optimize raw data by bypassing steps of the ETL process. Enable hassle-free data import via proprietary data caching technology
  • Centralized Data Warehouse: Creates a single source of truth by ingesting and storing data where it’s analyzed, speeding up analytics processes.
  • Ease of Use: Explore data and visualize trends through simple search query language, rather than via coding or modeling, making it an accessible solution for users of all technical skill levels.
  • Stats at a Glance: Understand and parse the results of data queries through Summary Statistics, without needing to write more SQL while exploring data and building models.
  • Reusable Analysis: Save time by storing frequently used in-house codes for swift collaboration without needing to start new queries from scratch.
  • Collaborative Insights: Enable collaboration between analysts and decision-makers through programming and self-service analytics combined. Hand off data analysis between teams, then publish and share insights with others via direct linking, password-protected links, email or Slack.
  • Self-Service BI: Pinpoint important data points in minutes, with reusable formulas and ad hoc analysis modeling that query data and return answers in real time.
  • R, Python and SQL On One Platform: Develop more advanced analytics processes with any programming language, with support for SQL, Python and R all in the same environment. Integrate open-source programming and formulas from other packages or libraries.
  • Scalability: Incorporate more complex datasets, higher volumes of data, more users and more, as the solution grows with the company.
  • Security: Have confidence in data security, with a cloud security infrastructure that upholds industry wide best practices and standards. Encrypt all traffic between users’ web browsers and Sisense’s servers, and for additional user-level security, manage data permissions, TFA and single sign-on functionality.
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  • Ease of Use: Make self-service analytics available to all via search-engine style natural language querying, intuitive and descriptive dashboards and visualization recommendations. Access data anywhere and everywhere through mobile support.
  • Data Security: Keep data safe from hacking and accidental leakage by restricting access via granular user privileges. Make onboarding easy by integrating with other single sign-on solutions and offering native support for company directories.
  • System Monitoring: Offer total visibility into the health of the system, including real-time and triggered alerts via pre-built administrative dashboards. Stay in the loop at all times by setting alerts on mobile devices or via email.
  • Collaboration: Easily share graphics, communicate about trends and discuss data models within the organization or with clients in real time via the one-click sharing feature.
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  • Native Data Connectors: Blend data together into a single accessible database via an ecosystem of native data connectors and ETL partners.
  • Cloud Data Pipelines: Control when and how often data is refreshed and what the flow of information looks like. Gain visibility and control over data pipelines with a flexible, low maintenance solution.
  • Data Discovery: Directly access CSVs and data sets curated by analysts and interact with these insights through a drag-and-drop interface that does not require fluency in SQL. 
  • Git Integration: Grant developers complete control over their analytics environment through Git integration, sophisticated version control, release management workflows as well as file-level access to all user-generated content, like reports. Create, edit, sync and delete all settings through Git. 
  • Model-as-You-Go: Perform ad-hoc analysis to answer crucial questions at the click of a button by generating custom, on-the-fly data models.
  • Data Visualization: Create and share advanced, highly customizable data visualizations, including scatter plots, bar charts, bubble charts, bullet charts, funnel charts, waterfall charts, control charts, Gantt charts, radial bar charts and more.
  • SQL Editor Tools: Shorten the amount of time necessary to go from query to answer with powerful SQL writing tools, such as query revision history, views, filters, autocomplete suggestions, formatting and more. 
  • Learn SQL: Experiment with SQL programming language and data querying via drag-and-drop fields and see how the results change. Encourage users who aren’t fluent in SQL to become more familiar with it.
  • Code Library: Reduce repetitive data entry tasks and save time for subsequent report generation. Store frequently used code in a common library via Snippets for easy access later. 
  • Spaces: Manage data-level permissions to gate and restrict access to sensitive data and customize dashboards on a per-organization basis.
  • Share and Embed: Share dashboards via password-protection enabled public URLs or embedding inside other web applications or web portals. Download dashboards as static PDF images for uses such as email distribution.
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  • Data Connectors: Draw data from a range of data sources via native connectors or by leveraging an existing ETL solution. Load large datasets at speeds of up to 1 terabyte per hour.
  • Embeddability: Deploy as a stand-alone platform or embed into other business software applications, such as CRMs or ERPs. Draw data and interact with it without switching interfaces to a separate login page.
  • Distributed Cluster Manager: Optimize workload distribution and scale it as the organization grows. Retain data and system usability at all times with built-in replication features, data redundancy assurances, as well as automated backups and node failovers.
  • Visualization Suggestions: Offers suggestions for best-fit visualizations based on data characteristics. Create intuitive graphics that help communicate patterns and draw insights.
  • Automatic Search Index: Indexes search history and data, then caches it for easier search performance. Provides search suggestions based on each character typed into the search feature.
  • In-Memory Engine: Performs all calculations in-engine. Assure query performance with built-in search result caches and retrieve results across various sources and records almost instantaneously. Organize data for efficient data exploration and retrieval.
  • Search Inspector: Explains how search terms are transformed into queries. Gain more transparency into the data exploration process.
  • Real-Time Calculations: Reduce the wait for insights; calculate answers in real time. Automatically joins, aggregates, filters and groups data into analytical results.
  • Drill-Down: Get a micro or macro view of data on an ad-hoc basis by drilling up or down across a data model without predefined drill paths.
  • Reusable Templates: Offers pre-built templates for data worksheets. Create and save a data model once, then recreate it for recurring reporting needs.
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Product Ranking

#16

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Business Intelligence Tools

#17

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Business Intelligence Tools

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User Sentiment Summary

Great User Sentiment 140 reviews
Great User Sentiment 492 reviews
87%
of users recommend this product

Sisense For Cloud Data Teams has a 'great' User Satisfaction Rating of 87% when considering 140 user reviews from 4 recognized software review sites.

89%
of users recommend this product

ThoughtSpot has a 'great' User Satisfaction Rating of 89% when considering 492 user reviews from 6 recognized software review sites.

n/a
4.2 (14)
4.5 (72)
4.3 (145)
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4.0 (2)
4.3 (33)
4.0 (2)
4.8 (4)
4.6 (162)
4.1 (31)
4.4 (167)

Synopsis of User Ratings and Reviews

Data Querying: Almost 77% of users who mentioned data querying and data modeling said that this solution allows them to perform data queries of almost any kind.
Data Visualization: Of the users who mentioned data visualization, about 75% said that this tool excels at creating easily understandable graphics and visuals.
Sharing and Collaboration: Approximately 88% of users who mentioned this feature said that this solution facilitates strong collaboration on data analysis internally, while allowing for easy external sharing.
Implementation: In reference to setting up the platform, about 90% of users said that the process was smooth and quick.
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Data Analysis: Citing the power of AI-driven natural language searches, approximately 86% of users say that this platform enables efficient self-service data visualization and analysis for better insights into business data.
Data Integration: Around 77% of users who review data source connectivity say that the solution integrates well with databases and data warehouses, both on-premise and cloud-based.
Functionality: Approximately 80% of users say that they are satisfied with the platform’s capabilities for fast and accurate self-service data analysis to display actionable insights.
Ease of Use: Approximately 94% of users reviewing its ease of use say that this solution is user-friendly and intuitive.
Speed and Performance: Citing speed and efficiency in handling large amounts of data, 96% of users say that they are satisfied with the tool’s performance.
Service and Support: Around 87% of users who mention customer support say that they are responsive and knowledgeable, and that the vendor is receptive to user feedback on new features and improvements.
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Reliance on SQL: While it excels in data querying, around 78% of users said that SQL knowledge is necessary to use this platform.
Self-Service Analytics: About 80% of users reviewing this feature said that data analysis is not truly self-service, requiring the involvement of a hands-on IT or analyst team.
Cost: Of the users who reviewed the cost of this tool, almost 86% of them found it too expensive, especially for smaller companies.
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Data Visualization: Around 61% of users reviewing this feature say that customization options for features such as fonts, layouts, colors and graphs are limited.
Training: Around 50% of users who mention training say that additional learning tools and best practices documentation would help in driving user onboarding and retention.
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Sisense for Cloud Data Teams is a powerful BI tool that excels in the hands of data analysts with coding knowledge. These analysts will be able to model, manage, prepare, manipulate and analyze data with ease. As the platform supports SQL, Python and R programming languages, the sky's the limit when it comes to extensibility, development and coding support. The platform allows for strong collaboration within an organization, designed to alleviate the time-consuming burden of reporting and data visualization on IT teams while allowing business users to access insights on their own time. Most of the features are built around making the analytics team’s job easier, with reusable code, built-in collaboration and more. The support team earned universal praise from users who contacted them, citing their swift, in-depth and informative answers as immensely helpful in resolving any issues they had with the solution. In addition to hands-on support, a speedy implementation process ensures that customers can get the platform up and running in no time. We found that users’ opinions of the platform’s functionality and ease of use differed significantly based on their own roles; analysts generally praised its robust data visualization and data querying features, while decision-makers often found it hard to use, due to the SQL language barrier. SQL is necessary for most functions, and even though there is a visual query editor that attempts to make SQL more accessible, some users said that the platform doesn’t do enough in this regard. Overall, users did agree that the tool makes it easy to collaborate with each other to bridge that gap, with most of the analytics being done on the technical end, letting business users simply access those results. Still, it’s difficult to accurately call Sisense for Cloud Data Teams a self-service analytics tool, as it requires an IT or analyst team’s involvement to truly shine. Additionally, the cost can be prohibitive to smaller businesses. Overall, Sisense for Cloud Data Teams can be extremely powerful in the right hands - for those who know SQL and how to use it, it’s a dream for querying data and delivering analytics, but for those who don’t have the necessary IT resources, it could prove difficult to fully maximize the value of this data solution.

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ThoughtSpot is a powerful and reliable solution with the capability to deep-dive into data with an impressive level of granularity to perform business data analysis. With its AI-powered offering, SpotIQ, this platform enables easy data querying with intuitive drop-downs and suggestions to retrieve relevant business data for analysis and presentation. In addition, users can save and share their queries with other users with one simple click. In-memory data caching makes for faster data retrieval and creation of data visualizations on the fly, though some users feel that the platform should have more formatting options for better dashboard customization. With the capability to transform massive amounts of data sets into real-time analytics in seconds, this platform has a user-friendly interface that affords even non-technical users the autonomy to use data to discover anomalies and trends with minimal effort. Astutely recognizing the latency inherent in moving data between data sources and analytics platforms, the solution now offers direct querying into the in-cloud data warehouse Snowflake via its offering - Embrace. Users praise the pricing model of this tool since the cost incurred depends on the storage space consumed, not the number of users. The solution does have its limitations, though. Quite a few users say that implementing natural language processing (NLP) requires a lot of pre-work and that AI-powered searches can slow systems down. Data models have to be specifically tailored to the platform, which makes them inflexible for reuse. Though the tool is supported by all major browsers, users can face UI or performance issues with using it on Internet Explorer. As uploading Excel files is still the best way to push data into the platform, data import can be time consuming. Users feel that updated technical documentation and reporting tool tips for the dashboard UI could help shorten the learning curve. Deployment can be challenging for small businesses without IT support. Some users who reviewed it based on cost feel that this tool can be expensive for mid-level businesses. To summarize, businesses can leverage ThoughtSpot’s excellent AI-powered capabilities to share dynamic, real-time data analyses with employees and clients to drive effective decision-making within their organizations.

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