Some of these tools started life as enterprise reporting tools and expanded to self-service BI. Others started out as self-service data visualization tools and may or may not have added advanced reporting. Some tools can read large datasets in place, from a data lake or Hadoop; others must import all data. Deployments may be cloud-only or allow on-premises installation.
Birst bills itself as Enterprise BI with blazing fast data discovery. The Birst architecture connects the entire organization through a network of interwoven virtualized BI instances on top of a shared common analytical fabric.
Birst has a multi-tenant architecture. It can be deployed in the public cloud, in AWS, or on-premises as a virtual appliance.
According to Gartner, three quarters of Birst’s reference customers said it was their only enterprise standard for analytics and BI, and that 98 percent of Birst reference customers expect to continue using the product. Both are impressive expressions of support from users. On the other hand, Gartner reports that a large portion of Birst’s reference customers are using the product primarily for parameterized dashboards and reports, with only small portions using the product for more sophisticated analytic tasks. The product does support complex data models.
Domo combines a large assortment of data connectors, an ETL system, a unified data store, a selection of visualizations, integrated social media, and reporting into one online BI tool. It is aimed directly at senior executives and line-of-business users who need an intuitive business-facing dashboard. Domo claims to be more than a BI tool because its social media tool can lead to “actionable insights.” But, in practice, every BI tool either leads to actions that benefit the business or it ends up getting tossed onto the rubbish heap so that is hype is to be taken with a grain of salt.
Domo is, however, a very good and capable BI system. It stands out from the others by offering support for lots of data sources and lots of chart types. The integrated social media feature is nice despite the hype. However, Domo is harder to learn and use than Tableau, Qlik Sense, and Power BI, and at $2,000 per user per year it is many times more expensive than other tools.
Microsoft Power BI
Microsoft Power BI is a suite of business analytics tools that run mostly on Azure and that connect to hundreds of data sources, simplify data prep, and drive ad-hoc analysis. It is also one of the lowest-cost BI solutions on the market, with a price of $9.99 per user, per month for Power BI Pro, a free Windows desktop analysis tool, and free mobile viewer apps. Power BI Premium, a virtual server priced from $4,995 per month depending on capacity, does not require named user licenses, and includes Power BI Report Server, which can be run on-premise.
Power BI scores high on ease of use, but according to Gartner the scores from its reference clients place it in the bottom quartile for breadth of use. Most of Microsoft’s reference customers (59%) mainly use Power BI’s parameterized reports and dashboards, rather than using it for more complex tasks. The average proportion of business users authoring their own content with Microsoft Power BI is 20 percent, which is very low.
MicroStrategy combines self-service visual data discovery and analytics with enterprise analytics and reporting that is suitable for large-scale systems of record. It offers a single integrated platform with many different license options for data consumer and power-user roles. Clients are available for web, desktop, and mobile. Servers are available for reporting, intelligence, in-memory analytics, transactions, distribution, collaboration, geospatial services, badges, and telemetry. Drivers are available for relational databases, OLAP, and Hadoop.
MicroStrategy has made a long slog from its historical focus on enterprise reporting to now also being able to satisfy self-service users and to enable easy departmental deployments on AWS. Outside of its customer base, however, it remains almost unknown.
Qlik Sense offers governed data discovery, agile analytics, and BI. And it uses a scalable associative in-memory engine that can also be used as a data mart. It can also provide enterprise reporting using its optional Qlik NPrinting server module.
When working with Qlik Sense, you can save a bookmark to the current selection in the current sheet. Then you can combine bookmarks into stories and add text and other annotations to make the story self-explanatory. If you’re using a story for a live presentation, you can drill down to the source for any visualization to answer — and illustrate — questions that come up. Once you have answered the question, you can easily return to the story.
Qlik’s associative green-white-grey experience in which colors of displayed values indicate state (selected-selectable-not selectable) helps you to spot both related and unrelated data without having to dig — a very nice touch. Qlik claims that its associative engine can discover insights that query-based BI tools miss. The Qlik DataMarket gives you access to curated external data that you can use to augment and cross reference your internal data.
Salesforce Einstein Analytics
Salesforce Einstein Analytics gives you a clear view into your Salesforce data, helping to highlight critical performance metrics and trends. The Einstein Analytics Platform lets you build custom point-and-click interactive visualizations, dashboards, and analysis with integrated self-service data preparation using Salesforce and (for more money) non-Salesforce data. In addition, Salesforce Einstein offers specialized apps for sales, service, B2B marketing, and AI-assisted discovery.
SAS Visual Analytics
SAS, a company better known for its data science and statistical analysis products, offers SAS Visual Analytics, which provides interactive reporting, visual discovery, self-service analytics, scalability, and governance, using an in-memory environment. It includes predictive analytics to assess possible outcomes and make data-driven decisions, which SAS claims is easy enough for a business analyst.
SAS Visual Analytics can be deployed on-premises, in SAS data centers, or in the public cloud. It is strong on interactive visual exploration and analytic dashboards. It supports advanced chart types as well as advanced analytics, and allows for R, Python, Java, and Lua models as well as SAS models.
Sisense is an integrated, end-to-end, analytics and BI platform, built on an in-memory columnar database, offering visual data exploration, dashboards, and embedded advanced analytics features. Sisense can be deployed on-premises; in public, private, or hybrid cloud; and as a managed service.
One differentiator claimed by Sisense is that it makes heavy use of on-CPU memory (cache) to move data 50-100 times faster than in RAM. While Sisense emphasizes its scalability, its average deployment size is 300 users, according to Gartner.
Tableau is an analytics platform as a service with strong visual data discovery. The base platforms are Tableau Server (Windows or Linux) and Tableau Online (hosted). Users can be Creators, Explorers, or Viewers. Creators have licenses to the Server or Online versions, as well as to Tableau Prep (data preparation) and Tableau Desktop (Windows and macOS).
Tableau also offers two free desktop apps for Windows and macOS: Tableau Public and Tableau Reader. Tableau Public can both open and create analyses that reside on your Tableau Public profile. Tableau Reader can open and interact with data visualization files built in Tableau Desktop.
Thoughtspot features a search-based approach to visual analytics and the ability to integrate, prepare and search billions of rows and terabytes of data. Thoughtspot claims it can respond in seconds to searches of billions of rows. It accomplishes this with an in-memory, massively parallel processing (MPP) columnar database and a distributed cluster manager.
Thoughtspot also sports SpotIQ, an “AI-driven” analytics, that users can run on the query result data to uncover anomalies, trend lines, clusters, and other data features using statistical and machine learning algorithms. SpotIQ generates natural-language narratives for any insights it uncovers. If this sounds like the Google-ization of BI, that’s not an accident: several of the founders are Google alumni.