Sisense For Cloud Data Teams vs Infor Birst

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Our analysts compared Sisense For Cloud Data Teams vs Infor Birst 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
Infor Birst 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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Infor Birst is a cloud-based analytics software tool that aims to help users discover insights without the need for analyst input. It unifies IT-managed enterprise data with user-owned data, supporting the blending of both in a top-down and bottom-up manner. It uses consistent business metrics to structure raw data into organized sets and visualizations. It helps users identify patterns and better understand their organization’s KPIs.

It offers a seamless, integrated UI that allows users to perform every step of the data analysis process in a single interface, enabling a smooth experience. It can be deployed either from the cloud or self-hosted on-premise.

Users can purchase it in three available formats: per-user fee, by department or business unit or by end-customer in embedded scenarios.

To explore other popular solutions that Infor offers, visit our Infor company page.
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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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  • Scalability on Demand: Prevents data bottlenecks caused by data loads that exceed capacity as business grows by scaling as needed through a multi-tenant architecture across a multi-node environment.
  • Faster Results: Delivers faster analytics across the entire organization by utilizing automated data analysis technology, cloud architecture and reusable metadata.
  • Data Clarity: Promote data clarity and reduce ambiguity by offering unique views into data to help everyone, regardless of technical expertise. Better understand the meaning of individual KPIs via the semantic layer, a set of shared business definitions.
  • Self-Service: Gives employees at all levels of technical skill self-service tools, such as drag-and-drop, to explore, analyze and visualize data through the user-oriented UX.
  • Informed Decisions: Make more data-driven business decisions by better understanding operations. Identify trends in business data by collecting, organizing, exploring and visualizing data.
  • Predict Future Outcomes: Generate actionable insights by leveraging AI to analyze historical data and improve business moving forward.
  • Intuitive Visualizations: Easily interpret trends by cleaning data and building understandable visualizations through machine learning.
  • Networked BI: Builds collective intelligence. Combines IT-managed enterprise data with user-generated data and eliminates data silos, unifying data from every part of an organization.
  • Certified Security: Secures data at every degree of detail, down to the row and column level. Employs strict data security protocols and procedures to protect data in  processes and data centers, which are certified for ISO27001 and SOC II, TYPE II standards and compliant with EU Safe Harbor laws.
  • Free Trial: Try it hands-on via a free trial.
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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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  • Automated Data Refinement: Automatically merge data from different sources into one user-ready data storage and optimize it for analysis. 
  • Semantic Layer: Boosts trustworthiness of data and reduces data anarchy by adding an agile semantic layer between the user and data. Work with data privately while staying connected to the network via a virtual tenant space.">
  • Real-time Access: Directly query on-premise data sources in real-time, eliminating the need to first extract and then upload data to the cloud.
  • Adaptive UX: Create reports and dashboards without coding knowledge via intuitive drag-and-drop tools. Supports different analytic styles, such as visual discovery, and mobile, and third-party tools such as Excel, R and Tableau. 
  • Reusable Rules: Automatically generates a common architecture based on a reusable set of business definitions without manual intervention.
  • Interactive Dashboards: Explore data even further via interactive dashboards that have drill-down capabilities such as lasso filters.
  • Multi-Tenant Cloud Architecture: Scales vertically and horizontally with a multi-tenant architecture built on a multi-node environment. Speeds insight generation by reducing the overall time spent on repetitive on-premise tasks. 
  • One-Click Data Connectivity: Access existing data with one click via its extensive library of pre-built connectors.
  • Embedded Analytics: Scale with clients’ businesses via flexible deployment options including embedding, APIs and localization capabilities.
  • Machine Learning: Recognizes patterns in data via Smart Analytics and automatically builds visualizations based on predictive analytics. Learns over time, and remembers previous search queries, past visualizations and more.
  • Deployment Options: Deploy as a SaaS through the cloud or go hybrid, keeping data in-house but running analytics through cloud-based servers. Or, deploy through a virtual appliance that delivers all the benefits of a traditional cloud-hosted SaaS while being locally hosted on-premise or in a private-cloud.
  • Mobile App: Access reports and dashboards via its native mobile application for iOS and Android.
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Product Ranking

#16

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#22

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User Sentiment Summary

Great User Sentiment 140 reviews
Great User Sentiment 560 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.

82%
of users recommend this product

Infor Birst has a 'great' User Satisfaction Rating of 82% when considering 560 user reviews from 6 recognized software review sites.

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4.3 (7)
4.5 (72)
3.9 (92)
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4.08 (49)
4.3 (33)
4.1 (50)
4.8 (4)
4.1 (176)
4.1 (31)
4.2 (186)

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 Integration: About 80% of users who mentioned its data integration capabilities said that the platform, powered by built-in connectivity tools, connected well to many types of data sources.
Data Visualization: Approximately 81% of users who reviewed visualization said that the tool provided attractive and intuitive data presentation options for at-a-glance data analysis and trend charting.
Ease of Use: The platform was user-friendly and intuitive, according to around 77% of users who reviewed the interface.
Functionality: Approximately 68% of users who reviewed functionality said that the platform provided strong capabilities to streamline preparation and consumption of data for developers and end users alike.
Data Management: Automated data warehouse creation made data modeling a breeze, around 65% of users who reviewed the platform’s data management system said.
Setup: Around 69% of users who mentioned implementation said that the solution being cloud-based, coupled with excellent onboarding support from the vendor, made deployment easy.
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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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Performance: Approximately 87% of users who reviewed the platform’s performance said that it was slow and inconsistent in data processing and data refresh.
Learning Curve: About 81% of users who mentioned the learning curve said that documentation was often insufficient and incorrect, and that the platform’s use of proprietary language made the learning curve quite steep.
Service and Support: About 46% of users who reviewed this feature said that support was poor and turnaround times were painfully long, extending up to several months.
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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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Infor Birst is an integrated cloud-based end-to-end solution for sourcing raw data, and extracting, warehousing and reporting for enterprise data analysis. With built-in tools for data integration and strong embedded analytics capabilities, users leverage its data visualization capabilities to create and share metric-specific dashboards and reports. Users who reviewed data management said that automated data warehouse creation was a strong feature of the platform, as well as its user-friendly interface. Many users who reviewed its functionality said that, equipped with a powerful ETL and efficient ODBC drivers for integration, the platform was flexible and scalable with a multitude of features for data discovery and analysis. Around 69% of users who reviewed ease of implementation said that deployment was easy with the integrated cloud platform, though some users said that the setup processes were unclear and they required in-house IT support for onboarding. On the flip side, users who mentioned performance said that the speed of data processing and data refresh was slow and this impacted report generation capabilities. Documentation was inconsistent and often incorrect, and the use of proprietary query language made the learning curve quite steep, many users who reviewed this feature said. Support turnaround times were woefully long, even extending up to several months as reported by a number of users. Some users who reviewed functionality said that the code was buggy and the platform stalled often when processing data for ad-hoc reporting. Many users complained that these bugs were not addressed for years, and new releases often impacted pre-existing features. Possibly because of its performance issues with large amounts of data, quite a few users rate it as a good BI tool for small and midsize companies that require less complex data analysis, rather than larger enterprises. In summary, Infor Birst is a BI ecosystem with a networked approach to data visualization and predictive analytics that eliminates data silos and serves as a single source of truth for enterprise data.

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