According to Eckerson Group, “The invention of data warehouse automation (DWA) as a technology category was inevitable. And it was invented in a real sense: the first DWA tools evolved to address gaps in the development, deployment, and maintenance of data warehouse systems.” Data warehouse automation was (and still is) necessary because data warehouses are always designed for a specific set of data and specific set of needs for an individual organization.
As the use of data warehouses change and their place in analytics shifts, data warehouse automation tools are also evolving. A new research report by Eckerson Group looks more closely at the history of data warehouse automation, what it is and what it does. The report, “Deep Dive: Data Warehouse Automation” by Stephen Swoyer also includes a deep dive into the capabilities of TimeXtender Discovery Hub.
The report states that data warehouse automation tools do three things:
Data warehouse automation tools drive cost reduction by increasing productivity of those building a data warehouse, “Generally speaking, a developer, data modeler, architect, etc., will be able to do more work in less time using a DWA tool than using a mix of point solutions and custom coding.” Also important for developers of data warehouses is that “a DWA tool aims to eliminate (or, at least, to minimize) the need for human-maintained artifacts, including scripts, procedural code, macros, documentation, or virtually any other supporting or enabling asset that requires human oversight or ongoing maintenance.”
In case you are not familiar with them, Eckerson Group is an independent research, consulting and education firm that focuses solely on data analytics. Their veteran practitioners each have more than 25 years of experience in the field. They specialize in every facet of data analytics—from data architecture and data governance to business intelligence and artificial intelligence. Eckerson Group recently wrote a new research report
The report includes a deep dive into the capabilities of TimeXtender’s Discovery Hub, and concludes, “Discovery Hub is intended to function as a foundation for analytical use cases of every kind, from traditional data warehouse development to self-service BI, discovery analytics, and data-scientific research and development. The Discovery Hub architecture is at once forward-thinking and common-sense. It’s so common-sense, in fact, that the rest of the industry seems to be coming around to its logic, if not its inevitability.”
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