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Why Automate the Data Warehouse?

Accelerate ingestion, save time and money, reduce errors.

I had the opportunity to speak with Stan Geiger, Director of Product Management at IDERA Software and Chris Taylor, Director of Support, Service and Training at WhereScape.

IDERA acquired WhereScape in September to expand its product offering to data warehouse automation. Automating the data warehouse accelerates development from design, to recreating history, and landing high-speed data into

streaming, unstructured data into a vault. A vault is a different paradigm for storing data. You are not limited by tables or business rules and you don’t assign them until you are ready to query and export.

The solution is ideal for the data warehouse team being challenged to manage more data, more quickly with fewer resources. The speed with which organizations are expected to deliver real solutions is accelerating, speed to value is essential, as is data-driven decision making with real-time analytics.

Companies are shifting to hybrid multi-cloud platforms and cloud-based databases that others can manage optimized to handle a lot of data.

There are five key benefits to automation:

  1. Quality - able to meet business requirements, standards enforcement, and automated regression

  2. Agility - react quickly to changes in business needs, changes do not accumulate where they create featureless major releases

  3. Cost Savings - development, operations, and maintenance

  4. Faster Development - fail fast and discover issues with business requirements or data quality

  5. Overall Operations - up-to-date documentation, better deployments

Use Cases

  • Rabobank wanted to build a data warehouse that met regulatory reporting requirements with a control framework, data quality management, and archiving. WhereScape’s out-of-the-box documentation capabilities and templated framework provided an automated data warehouse a tested structure. Releases that used to take two weeks now take two hours. Data automation changed the dynamic in the data team to save time and effort on repetitive tasks.

  • IQVIA manages data from hospital logistics, finance, HR, and other sources. When the data team rolled out a new release, they had to update 40 to 80 environments. Each customer had their own sources and choice of modules. Hand coding was a lot of work. IQVIA considered ETL tools like DataStage and SSIS but discovered Data Warehouse Automation. Adding a column or dimension used to take five to 10 steps using different tools. Now it takes two minutes letting automation regenerate the code and commit the required changes. There is no chance of human error and reports and documentation make lineage impact analysis clearer and easier.

  • As Fidelity Bank expanded, so did the complexity and volume of data. Fidelity realized the need to evolve their data infrastructure strategy. They used WhereScape automation for Teradata to design and build an enterprise data warehouse. Automation was built specifically to leverage the capabilities of Teradata. Fidelity Bank was able to deliver its first data warehouse in less than four months with one developer with no previous Teradata experience.


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