Analyst Perspectives

Organizations are collecting vast amounts of data every day, utilizing business intelligence software and data visualization to gain insights and identify patterns and errors in the data. Making sense of these patterns can enable an organization to gain an edge in the marketplace and plan more strategically.

Tableau is a data visualization software company, acquired by Salesforce in 2019, that offers tools for data analysis and BI. It can enable an organization to analyze large volumes of data from multiple data sources and create interactive and sharable reports. It offers access to numerous data sources, including Amazon Redshift, Cloudera, Snowflake, Teradata and Google Cloud. Its platform enables line-of-business workers across the organization to use BI tools to visualize and understand raw data.

Organizations have to structure, shape and manage data from multiple sources and prepare it for analysis. Our Analytics and Data Benchmark Research found that organizations spend significant time preparing data for analysis, reviewing data for quality issues and preparing reports. Tableau Prep is a self-service data preparation solution that offers the capability to combine, shape and clean data for analysis within Tableau. It connects to on-premises data or cloud data, and can potentially reduce the time workers spend cleaning and organizing data sources. It offers a visual interface through which line-of-business workers can clean, automate and administer data from within the dashboard.

VizQL is Tableau’s visual query language for databases that translates drag-and-drop actions into data queries and then presents the findings visually through dashboards and data visualizations. Its live query technology can connect to large volumes of data in its existing format and location, including databases and cloud applications. It enables line-of-business workers to connect their existing data platforms to Tableau.

Organizations are expanding BI capabilities to democratize analytics and make insights more accessible. We assert that by 2024, one-half of organizations will include guided analytics processes and storytelling capabilities to help create and deliver insights for line-of-business personnel. At its 2022 conference, Tableau announced new features for guided analytics, including simplified, self-service tools like Data Stories, smart suggestions through Einstein Discovery and collaboration tools to work on shared data models.

Data Stories uses natural language query to generate explanations of Tableau dashboards. The feature is the result of Tableau’s 2021 acquisition of Narrative Science. Personnel can use its drag-and-drop feature to create a data story of the desired dataset, and then use a set of customizations to format and share it across the organization.

Since Salesforce acquired Tableau, the two organizations have worked to incorporate Salesforce’s Einstein Analytics with Tableau, rebranding it as Tableau CRM and, eventually, as CRM Analytics. With this integration, Salesforce enables users to combine the visual analytics capabilities of Tableau with the artificial intelligence and machine learning capabilities of Einstein Analytics. The company has also worked to bring more of the Einstein AI/ML capabilities into Tableau products, making it easier for business users to access AI/ML. For analysts and data scientists, it offers AI capabilities, what-if scenario planning, guided model building, insights and other data science techniques.

Tableau has also invested in Developer Program, which includes application programming interfaces and software development kits to enable users to extend and customize Tableau’s functionality. The APIs and SDKs help organizations create embedded analytics applications, which can help serve additional personas beyond analysts, an important step to expanding adoption and satisfaction with analytics, as I discussed previously.

Tableau continues to operate as an independent brand while benefiting from some of the technologies – like Einstein – that Salesforce has created. It has enhanced its ability to address more of the analytics spectrum with Tableau Prep. And it has expanded its appeal to larger portions of the workforce with natural language processing, storytelling and embedded analytics. Organizations looking for a platform to address a broad range of analytics requirements should consider evaluating Tableau.

Regards,

David Menninger