Whitepaper · Free access
When a Data Catalog is Not Enough: The Case for the Self-Service Analytics Workbench
Joe Hilleary
January 22, 2021
Data catalogs provide valuable information about data assets, but businesspeople want answers to questions, not just metadata. An emerging technology —the self-service analytics workbench—extends the data catalog with other self-service functionality and built-in workflows to meet this need. It supports the entire...
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What's Inside
What you'll learn.
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.
By consolidating multiple tools into a single workflow-enhanced platform, self-service analytics workbenches speed time to insight and improve communication between business users and the data analysts and engineers who support them. They eliminate the need to buy, learn, and integrate multiple disparate tools to enable the question-to-answer workflow, making the process of answering ad hoc questions more natural and efficient.