The Tableau platform is a set of business-user-friendly analysis, data visualization and data preparation tools. Its core comprises a full client and a web server with connectors to a wide variety of data sources, including local data. Its structured, intuitive user interface, built-in intelligence and memory utilization to optimize performance contribute to its popularity for self-service BI (SSBI), data discovery and interactive dashboards.


Tableau Software emerged from research at Stanford University, where its three founders aimed to provide business users with software that allowed intuitive visual analysis and insights into data. Tableau’s product strategy of bringing analytics to the masses clearly reflects this vision. However, the strategy today encompasses more than that. Tableau continues to evolve into a modern and open platform that is not only functionally enhanced, but also incorporates data management in a modern architecture.

In June 2019, Salesforce acquired Tableau to extend its analytics offering. Salesforce currently operates a worldwide business with more than 49,000 employees. As part of Salesforce, Tableau is positioned to accelerate and extend its mission to help people view and understand data. Tableau continues to operate independently under the Tableau brand, driving forward a continued focus on its mission, customers and community. Besides Tableau, Salesforce offers Einstein Analytics, which is tightly integrated into the Salesforce CRM suite, the major target of the vendor’s AI investment and clearly focused on providing customer analytics.

Tableau Platform is the common technology supporting four major products: Tableau Desktop, Tableau Server, Tableau Mobile, Tableau Prep Builder and Tableau Online. This review does not cover Tableau Public due to its limited relevance for enterprise use, nor does it examine Einstein Analytics due to its focus on providing analytics within the Salesforce suite.


Tableau strives to deliver software that is as intuitive as possible and requires little training but still allows business users to thoroughly analyze complicated data through visual analysis without having to rely on the assistance of BI developers. The toolset provides capabilities geared to analysts for in-depth analysis such as predefined statistical functions and data preparation capabilities.
The company previously pursued a “land and expand” strategy with a focus on business users, popular with other self-service BI vendors too. More recently, Tableau is devoting more attention to data management by introducing new features and enhanced support for enterprise environments.

In addition to the Tableau Desktop and Tableau Prep trial versions, Tableau offers a free software known as ‘Tableau Public’. This can be used to analyze, visualize and finally publish data to the Tableau Public cloud. Visualizations can be embedded into websites with complete interactivity retained (e.g., for data journalism or blogging).

Tableau’s original products were Tableau Desktop and Tableau Server. Tableau Desktop is the main authoring software, supporting the user through all steps of the analytics cycle (from data to insight). Tableau Server is the web and mobile-enabled dashboard publishing and collaboration environment. With this architecture, customers typically have a few power users who produce analytics content and a much larger share of casual users who consume reports, dashboards and analyses. Tableau has many reference customers for deployments supporting thousands of users.
Tableau Online is the multi-tenant cloud solution, which is the hosted version of Tableau Server. The product works with on-premises as well as cloud data sources. It is typically used to quickly start or scale analytics to many users without requiring huge IT involvement.

Tableau has various types of technology partners. It partners with database and application vendors such as SAP, Cloudera and others by building native connectors to these systems. Partnerships with companies like Informatica and data preparation vendors such as Alteryx support customers’ data integration needs. Tableau also partners with specialists to extend the product’s capabilities (e.g., with Datasift to provide social sentiment analysis). Finally, Tableau can connect to R, Python, SPSS and SAS data sources for advanced analytics (e.g., cluster analysis, decision trees).


Tableau Desktop builds on a proven client-server architecture based on integrated columnar and optimized data storage. The underlying database (Hyper) has been available since the acquisition of Hyper in 2016. Customers can use the in-memory engine to speed up extract creation and analysis. The core authoring component is Tableau Desktop, but features are increasingly incorporated in Tableau Server, offering even data preparation on the web. Advanced and better guided data preparation are done in Tableau Prep Builder, which is being continuously enhanced (e.g., to write data to external databases). Tableau Prep Builder can be extended with Tableau Prep Conductor, a server component that is used to schedule and automate data flows.

Tableau offers connectivity to a huge number of sources available in Tableau Desktop. In addition to relational and multidimensional databases, on-premises and cloud business applications can be accessed too. Tableau is also capable of integrating local files with capabilities to parse and import data from tables in PDF. There are functional differences between relational (SQL) and multidimensional (MDX) data sources. Some features are not available when connecting to OLAP data sources but can be used when connecting to relational data sources and vice versa.

Tableau supports two paths to connect to data sources. ‘Live connect’ leaves data in the underlying data store and queries the data at runtime. In this case, Tableau acts as a pure front-end analysis tool and does not store the data. The second and much more common option is to use Tableau’s own integrated data storage ‘Hyper’ to create optimized extracts and to load data into memory. Using a Hyper extract is beneficial when the underlying database is slow, if a user wants to reduce the load on the underlying system, or when a user wants to work with data offline. Replicating data may require replicating security settings too and can be a challenge for proper data governance. To increase flexibility for Tableau and Hyper users, the vendor is opening its platform to third-party providers by offering access to Hyper.

Tableau Server is the solution’s application server and acts as a central repository and portal for all Tableau metadata concerning users, data connections and content. Tableau Server administrators can perform tasks such as refreshing data sets and managing users and published content. Metadata is stored in an internal database. Tableau Server also allows users to consume and interact with – and even modify – published visualizations on their web or mobile clients. Administration is also possible via the browser with Tableau Server Manager (TSM). In addition to Tableau workbooks, dashboards and views, users can also access published shared data sources to create new analyses.

Tableau continually aims to enhance scalability, security and administration of large enterprise environments. To evolve the product further towards a full stack enterprise platform, Tableau introduced Tableau Catalog as part of its enhanced data management offering. Tableau Catalog is Tableau’s own data catalog solution and is packaged with Tableau Prep Conductor as a data management add-on for Tableau Server. Relationships were introduced to increase flexibility during analysis by joining data during analysis instead of in the data source. Queries retrieve less data, which speeds up analyses and data duplication is avoided through ‘understanding’ the granularity of data.

Front-end functionality

Most Tableau content producers and consumers are business users rather than data scientists or BI developers. Data access and preparation are performed in Tableau Desktop, or increasingly Tableau Prep Builder, using a graphical interface with built-in intelligence to assist users. Tableau automatically recognizes data types and creates hierarchies for date fields.

Tableau’s primary focus is interactive and intuitive visual analysis to efficiently dissect data and find patterns. Measures and dimensions are selected via drag-and-drop for analysis and visualized instantly in interactive visualizations. Users are guided by the software with functions such as ‘Show me’, which proposes appropriate visualizations for any combination of data fields selected. Tableau offers grouping, hierarchizing and calculation options supported with context-sensitive wizards. Its calculation library’s analytical feature set ranges from simple trend to smoothed forecasts, table calculations and other analytical and statistical functions such as cluster analysis that are easy to apply without requiring coding.

Visualizations reside in individual sheets in Tableau, much like the sheets in an Excel workbook. To create a dashboard, the users drag worksheets from a shelf onto the dashboard canvas and rearranges the visualizations. Users can extend the information on a dashboard by linking to further information on the web via a “URL action” or dashboard extensions. Tableau also possesses a parameter and global filter concept, which allows dashboard consumers to intuitively filter the data displayed to a specific range. In addition, Tableau provides features for data-driven alerts and custom content subscription.

Visualizations and dashboards are optimized for screen display rather than for printing. Tableau offers limited functions to specify page formats and control printer output. Printing takes place according to the WYSIWYG principle. Workbooks can be printed out or exported to PDF, Excel and CSV, distributed as files via email or URL, or embedded into a website or portal.

In Tableau Server, users can collaborate and discuss content via comments, annotations and dashboard web page objects. Fields can have comments that further describe them. Annotations can be used to call out specific highlights such as values on an axis or a reference line, or an area such as a cluster of scatter plot dots, which is important especially when compiling data stories in the relevant storytelling section. Conversations and annotations can be shared on Tableau Server alongside the applicable visualizations and dashboards to foster close collaboration based on governed information assets.

User & Use Cases

Tableau is popular in medium to large enterprises with above-average sized deployments. This year, respondents reported a median of 100 users, but the significantly higher mean value of 2,068 users indicates it is also used in much larger scenarios. Tableau deployments are maturing and serve a growing share of information consumers as well as an increasing number of users with interactive dashboards built on top of visual analyses. As deployments grow, the share of users creating reports or analyzing data declines as the proportion of consumers increases. This shows the continued importance of standardized content such as dashboards and formatted reports as well as the need to quickly satisfy ad hoc information requirements.

Current vs. planned use


5 products most often evaluated in competition with Tableau


Percentage of employees using Tableau


Number of users using Tableau


Tasks carried out with Tableau by business users


Company size (number of employees)


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Peer Groups Ad Hoc Reporting-focused Products, Dashboarding-focused Products, Large international BI vendors, Self-Service Analytics-focused Products
VendorTableau Software (A Salesforce Company)
Number of responses85
ProductTableau Platform
Employees49,000+ (Salesforce)
Customers150.000 (Salesforce)
Revenues (2019)17.1 billion USD (Salesforce)