Sisense For Cloud Data Teams vs Sigma Computing

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Our analysts compared Sisense For Cloud Data Teams vs Sigma Computing 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
Sigma Computing 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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Sigma Computing is an analytics solution that directly connects to cloud warehouses and delivers real-time insights that drive data-informed decision making. With a spreadsheet-like interface, it provides a familiar experience for business users and analysts to utilize formulas to analyze and visualize their data. Through a self-service model, users can explore their data and ask and answer questions for themselves. It streamlines complex data analysis processes and promotes teamwork throughout a business with a balance of collaboration and control.

It is entirely cloud-based and enables data access without the risk of extracting, moving and storing data. Suitable for companies of all sizes, this SaaS runs on Windows, Mac and Linux.

Pros
  • User-friendly interface
  • Affordable pricing
  • Scalable for business growth
  • Cloud-based accessibility
  • Responsive customer support
Cons
  • Limited data analysis features
  • Less powerful than competitors
  • Occasional performance issues
  • Restricted data storage capacity
  • Lower customization options
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Knowledge Base
24/7 Live Support
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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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  • Fast Integration: Without coding experience, users can securely and directly connect to data warehouses and get started without wasting valuable time on importing their data. Analysts can lay the foundation for the entire organization to succeed with data in hours, rather than days.
  • Ease of Use: Users work with a familiar spreadsheet-like interface and formulas to generate insights, no code required. The system automatically translates all the front-end actions input by users into SQL on the back-end.
  • Real-Time Access: Users can leverage the power of the cloud to query data directly where it lives, allowing for live analysis of massive datasets and insights in real time. 
  • Keep Data Safe: Sigma never moves, stores, copies or caches users’ data, instead running queries against the data warehouses and passing the results back to the system, ensuring that data remains secure with robust data governance and platform security that exceeds industry standards. It complies with data privacy guidelines SOC 2 Type II, CSA, GDPR and CCPA.
  • Improve Collaboration: The system eliminates BI bottlenecks and inaccurate analyses by establishing a single, reusable and accessible source of truth for all users to query. Sigma transforms the data modeling process into a collaborative one; users can edit tables and create visualizations together, enabling better communication and decision making by forging a bridge between data teams and business users.
  • Self-Service BI: Users have the freedom to explore ad hoc analysis without waiting for IT teams to update models.
  • SQL Authoring: Users with SQL technical knowledge can create and edit reusable analyses to activate with one-click parsing.
  • Free Trial or Demo: Interested customers can try out the full platform for free for 14 days, or request a demo of the solution to try with their own data warehouse.
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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 Warehouse Connectivity:  Sigma connects directly with many popular data warehouses, including Snowflake, Google Big Query, Amazon Redshift and PostgreSQL, or users may pull their data from other partners like Matillion, Fivetran, Alooma and Stitch to create their central source of truth by indexing all the tables in those sources. 
  • Dataset Preparation: Sigma creates reusable datasets from individual or joined tables using one or more data sources. These Datasets can be edited either with a no-code worksheet-based interface, or with Sigma’s SQL Runner. 
  • Links: Users can add context to their Datasets by setting up the relationships between datasets in a guided, contextualized way. Non-technical users can preview and create pre-model joins without needing knowledge of the join creation process. The system also pulls pre-existing relationships in databases upon connection with a data warehouse.
  • Data Visualization: Users can create assorted kinds of charts and graphs from their worksheets, including bar charts, line graphs, pie graphs, tables and more. These visualizations can be formatted in various ways. 
  • Object Badges: Users can flag datasets and worksheets as Endorsed, Warning or Deprecated, guiding others to the most accurate and relevant data with a glance.
  • Shareable Workspaces: The platform has both individual and team workspaces, allowing for collaboration on data analysis. These workspaces can be shared externally, providing access to insights to partners or third parties who may benefit from them. The system also has an organization-wide workspace that everyone can search and explore through filters, descriptions and file names.
  • Role-Based Permissions: The system has tiered permission levels from highest to lowest for admins, authors and viewers, to allow different permissions and access settings on a role-by-role basis. Permissions may be granted on an individual or team level, allowing for organizations to add and remove users from access levels based on function, department or other categorization.
  • Data Security: In addition to role-based access control, the platform provides single-sign-on (SSO) and row-level security to ensure safe data analysis. The application has a secure infrastructure, with firewalls, credential and vulnerability checking, peer review, static code analysis, threat and anomaly detection and encryption in transit.
  • JSON Support: The visual interface enables business users to create views with JSON that unlock the value of semi-structured data. These strings of JSON can be stored, referenced and reused for analyses and visualizations across the ecosystem. 
  • Third Party Integrations: The system integrates with Slack and Google Sheets for enhanced collaboration.
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User Sentiment Summary

Great User Sentiment 140 reviews
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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.

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4.5 (72)
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4.3 (33)
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4.8 (4)
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4.1 (31)
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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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User-friendly interface: Sigma's intuitive design and drag-and-drop functionality make it easy for users with limited technical expertise to get started and create insightful reports.
Affordable pricing: Sigma offers a competitive pricing model with a free tier for individual users and small teams, making it accessible to businesses of all sizes.
Scalable for business growth: Sigma's cloud-based architecture scales seamlessly to accommodate growing data volumes and user bases, ensuring your BI solution can grow with your business.
Cloud-based accessibility: Access your data and insights from anywhere, anytime with Sigma's cloud-based platform, eliminating the need for on-premise infrastructure.
Responsive customer support: Sigma provides responsive and helpful customer support via email, phone, and live chat, ensuring you get the assistance you need when you need it.
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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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Limited data analysis features: Compared to more robust BI solutions, Sigma offers a less extensive range of advanced data analysis capabilities.
Occasional performance issues: Some users have reported encountering occasional performance issues, such as slow loading times and data refreshes.
Restricted data storage capacity: Sigma's free and lower-tier plans offer limited data storage, requiring upgrades for larger datasets.
Lower customization options: While Sigma offers some customization options, its capabilities are not as extensive as other BI platforms.
Less powerful than competitors: Although Sigma excels in user-friendliness, it may lack the power and flexibility required for complex data analysis needs.
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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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While Sigma Computing receives praise for its user-friendly interface and affordability, some users feel it lacks compared to similar BI tools like Tableau and Power BI. One user noted, "Sigma is great for beginners, but I quickly outgrew its capabilities. It just doesn't offer the depth of analysis I need." Another echoed this sentiment, stating, "The lack of advanced features was a dealbreaker for me. While Sigma is easy to use, it's not powerful enough for complex data analysis." However, others find Sigma's strengths outweigh its weaknesses. One user commented, "For the price, Sigma is a fantastic tool. It's simple to use and allows me to create insightful reports quickly and easily. I don't need all the bells and whistles offered by other platforms." Another user praised its scalability, saying, "Sigma has grown with my business. As my data volume increased, Sigma seamlessly scaled to accommodate my needs." One differentiating factor is Sigma's focus on real-time data and collaboration. One user highlighted this, saying, "Sigma's ability to work with real-time data is a game-changer. It allows me to make decisions based on the latest information, not outdated data." Another user noted the benefits of collaboration, stating, "Sigma's collaborative features make it easy to work with my team on data analysis. We can share insights and brainstorm ideas in real-time." Ultimately, the suitability of Sigma Computing depends on individual needs and priorities. If you're a small business or individual user who needs a basic, affordable BI tool, Sigma is a great option. However, if you require advanced data analysis capabilities or extensive customization options, you may be better served by a more powerful BI platform.

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