Data Management at Scale, 2nd Edition

Chapter 11. Turning Data into Value

In this chapter, we’ll discuss most people’s favorite part of data management: turning data into value with intelligent services, such as business intelligence and advanced analytics. We’ll do this by focusing more on the consuming side of the architecture, while keeping in mind everything we’ve already covered about the data-providing side of the architecture. You learned that it takes a village to make data available in a safe and controlled way, with proper governance and security.

Let me immediately put my cards on the table: on the consuming side, use cases often need data to be combined from different domains and data products. This interaction is complex on both the technical and organizational levels. Therefore, I advocate for managing consumer-focused data differently from data products. The core concern here is bringing data together and combining it for different business use cases. It’s about turning data into value and using services that may be specific to the use case at hand. So, a large part of this chapter will be devoted to this topic.

The data-consuming side is also the most complex part of the architecture because each business problem has its own unique context and requirements. A large variety of tools, disciplines, roles, and activities are expected on the consuming side, which makes standardization difficult.

Business requirements always come first. Turning data into insights or actions requires understanding how information ...