The Tableau platform is a set of business user-friendly analysis and data visualization tools. Its core comprises a full client and a web server with connectors to a wide variety of data sources, including local data. The structured intuitive user interface, built-in intelligence and memory utilization to optimize performance contribute to its popularity in self-service BI (SSBI) and data discovery scenarios.
Tableau Software emerged from scientific research at Stanford University, where its three founders pursued a vision of providing business users with software that allowed intuitive analysis and insights into data. Tableau’s general 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 has a clear focus on data management and modern architecture.
Tableau’s corporate headquarters is in Seattle (US) and the EMEA headquarters is in London (UK). Over 4500 employees are located in 18 offices worldwide, with some branches still operating as pure sales offices. In June 2019, Tableau was acquired by Salesforce, a leading cloud based CRM vendor. As part of Salesforce, Tableau will be positioned to accelerate and extend its mission to help people view and understand data. Tableau will operate independently under the Tableau brand, driving forward a continued focus on its mission, customers and community.
Tableau Platform is the common technology supporting four major products: Tableau Desktop, Tableau Prep Builder, Tableau Server and Tableau Online. This review does not cover Tableau Public due to its limited relevance for enterprise use.
Tableau follows a strategy of delivering software that requires as little training as possible and allows business users to analyze data through visual analysis without having to rely on the assistance of BI developers. The tool offers additional analysis capabilities specifically geared to analysts for in-depth analysis such as predefined statistical functions and data preparation capabilities.
The company pursues a “land and expand” strategy with a focus on business users, popular with other self-service BI vendors too. With the 2019.3 update, Tableau is also devoting more attention to data management by introducing new platform features and better support for growing environments.
Tableau offers a free software known as Tableau Public in addition to trial versions of Tableau Desktop and Tableau Prep. Anyone can use Tableau Public to visualize data and publish it to the Tableau Public cloud. Visualizations can be embedded into websites with complete interactivity retained (e.g., for data journalism or blogging).
Tableau’s initial 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 developers (power users) 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 for analysis scenarios without IT involvement or sharing analysis results with users outside the firewall.
Tableau has various types of technology partners. It partners with database and application vendors such as SAP, Cloudera, Salesforce.com 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 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 has a proven client-server architecture based on optional, proprietary 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 simple data preparation over the web since version 2018.1.
Tableau offers connectivity to an unrivaled number of sources available in Tableau Desktop. In addition to relational and multidimensional databases, on-premises and cloud business applications can be accessed. Tableau is also capable of integrating local files with capabilities to parse and import data from tables in PDF.
There are functional differences when connecting to data sources due to the underlying language differences between MDX and SQL. As a result, some features are not available when connecting to OLAP data sources but are available when connecting to relational data sources and vice versa. Data source definitions can be re-used or published on the Tableau Server.
Tableau has two different ways 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 data storage facility 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. In order to increase flexibility for Tableau and Hyper users, the vendor is currently working on opening up the platform, including the Hyper database, to third-party providers.
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 PostgreSQL database. Tableau Server also allows users to consume and interact with and even modify published visualizations on their web or mobile clients. Since version 2018.2, 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.
Most Tableau users are non-technical 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. Entities such as 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. With version 2019.3, users will also have access to “Explain Data”, a feature which provides them with automatically created calculations, visualizations and natural language explanations for requested KPIs. Explain Data calculates insights based on AI-driven algorithms in 2018.
The tool offers additional grouping, hierarchizing and calculation options supported with context-sensitive wizards. Tableau’s 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.
Visualizations reside in individual sheets in Tableau much like the sheets in an Excel workbook. To create a dashboard, the user drags his chosen 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 introduced in version 2018.2. 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 describe them. Annotations can be used to call out a specific highlight such as a value 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.
User & Use Cases
Tableau is quite popular in medium to large enterprises with above-average sized deployments. There is a median of 187 users per Tableau customer, but the significantly higher mean value of 809 users indicates it is also used in a number of much larger scenarios. Tableau deployments are maturing and serve a growing share of information consumers. Tableau’s strengths lie in the simple visual presentation of information and navigation in data for analysis purposes, which also happen to be the main use cases and tasks that users perform with Tableau. It shows the increasing importance of viewing standardized content such as dashboards and formatted reports as well as the need to quickly satisfy ad hoc information requirements.
Current vs. planned use
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