Data warehouse automation (DWA) helps IT teams deliver and manage much more than before, much faster, with less project risk and at a lower cost by eliminating repetitive design, development, deployment and operational tasks within the data warehouse lifecycle.

The Data Warehouse Institute (TDWI) defines data warehouse automation as:
“…using technology to gain efficiencies and improve effectiveness in data warehousing processes. Data warehouse automation is much more than simply automating the development process. It encompasses all of the core processes of data warehousing including design, development, testing, deployment, operations, impact analysis, and change management.”

With automated data warehousing, IT teams can fast-track new data integration, more effectively work with big data, and devote greater time to the business intelligence initiatives that will yield the greatest impact for their organizations.

Data Warehouse Automation Benefits

Data warehouse automation provides data warehousing teams with a wide range of benefits commonly associated with digital transformation as seen in the diagram above.

Increase Productivity

Data warehouse automation has been credited with boosting developer productivity by fivefold. With the ability to automate as much as 80 percent of the data warehouse lifecycle, IT teams can more quickly deliver data warehouses, as well as more easily adapt existing data warehouses as business needs change.

Reduce the Learning Curve

When designed for a specific data platform, or data warehouse software, data warehouse automation can also greatly reduce the learning curve associated with implementing a new data platform within an organization. Whereas traditionally developers hand-coding projects would need deep knowledge of many aspects of the new platform, data warehouse automation specifically designed for the platform can mask much of the complexity working behind the scenes.

Standardize Best Practices

Data warehouse automation solutions have also been credited with providing organizations with the best practices standardization that can easily be lacking when working with a variation in development approaches, methodology understanding and other staffing characteristics. Thorough documentation is also a valuable takeaway for organizations using data warehouse automation, and often a luxury for those who are not.