Automating Data Transformations

Enable Your Organization to Solve the Largest Bottleneck in Analytics

Book Details

Book Description

The modern data stack has evolved rapidly in the past decade. Yet, as enterprises migrate vast amounts of data from on-premises platforms to the cloud, data teams continue to face limitations executing data transformation at scale. Data transformation is an integral part of the analytics workflow-but it's also the most time-consuming, expensive, and error-prone part of the process.

In this report, Satish Jayanthi and Armon Petrossian examine key concepts that will enable you to automate data transformation at scale. IT decision makers, CTOs, and data team leaders will explore ways to democratize data transformation by shifting from activity-oriented to outcome-oriented teams-from manufacturing-line assembly to an approach that lets even junior analysts implement data with only a brief code review.

With this insightful report, you will:
- Learn how successful data systems rely on simplicity, flexibility, user-friendliness, and a metadata-first approach
- Adopt a product-first mindset (data as a product, or DaaP) for developing data resources that focus on discoverability, understanding, trust, and exploration
- Build a transformation platform that delivers the most value, using a column-first approach
- Use data architecture as a service (DAaaS) to help teams build and maintain their own data infrastructure as they work collaboratively

This book is published as open-access, which means it is freely available to read, download, and share without restrictions.

If you enjoyed the book and would like to support the author, you can purchase a printed copy (hardcover or paperback) from official retailers.

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