All self-service tools available to data analysts will converge into a single workbench: data catalogs, data preparation, data visualization, and autoML tools. And these integrated toolsets will appear as stand-alone products as well as baked into data platforms, BI tools, and ETL tools.

Today, these ratios [of analyst workloads] are changing thanks to the advent of a triumvirate of specialized, self-service technologies designed explicitly for data analysts: data visualization, data preparation, and data catalogs. Together, these three technologies, along with an underlying data connectivity layer, form the basis of an emerging self-service, data analyst workbench. Today, companies purchase these products separately and stitch them together. But soon, they will be able buy an integrated solution from a single vendor that supports the entire data analyst workflow.

A self-service analytics workbench integrates a variety of analytics capabilities into a single platform. These include data catalogs, data virtualization, data preparation, and data visualization. These functionalities support every step in the process a data analyst or engineer goes through to answer business questions: search and examine data, extract and join tables, format and transform data sets, and visualize and publish results. In addition, self-service workbenches provide built-in workflows that connect business users who have questions with data analysts and engineers who can answer them.