A data warehouse is a way to provide business analysts and other users with a centralized repository of enterprise data from which to glean insights that guide business decisions.
What’s changed since data warehousing was first introduced in the 1970s is that traditional, waterfall data warehousing software development processes are no longer viable for planning, designing, developing and operating data warehouses. The traditional approach has proven to be too slow, too manual and too complex to deliver what the business needs, when it needs it. That's where data automation and data warehouse automation solutions can help.
Data warehouse automation 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.”
Data warehouse automation software combines the use of metadata, data warehousing methodologies, pattern detection and more to help developers autogenerate data warehouse designs and coding through the use of data warehouse design tools and timesaving development wizards and templates. By using data warehouse automation to address much of the time-intensive, repetitive work previously required in the hand-coding of data warehousing software projects, developers can instead focus on more strategic elements of data warehousing, and ensuring the data warehouse delivered will meet the evolving needs of the business.
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.
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.
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.
Deliver new data warehouse projects in days or weeks instead of months and years. From design through operation, automation can help you reduce the data warehouse development lifecycle by 80 percent, increase developer productivity five-fold, better collaborate with business stakeholders and respond more quickly to change.
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