Summary

Applying a Data Fabric architecture with a DataOps framework dramatically raises the bar to deliver data with high agility, quality, and governance at a lower cost. In this chapter, we provided an introduction to DataOps, its value, and the 18 driving principles. We briefly introduced Agile, SPC, and DevOps from which DataOps borrows many of its principles. We reviewed the distinction between traditional Data Quality and modern Data Quality, and how modern Data Quality can leverage a foundational Data Quality framework. We also defined data observability and its relationship to Data Quality. We concluded by conceptualizing the use of a Data Fabric architecture together with a DataOps framework. Both offer tremendous value and should be applied in the life cycle management of data.

At this point in the book, we have introduced Data Fabric, Data Mesh, DataOps, and foundational Data Governance concepts. In the next chapter, we will focus on a key business artifact, a data strategy...