Practical DataOps: Delivering Agile Data Science at Scale

© Harvinder Atwal 2020

H. AtwalPractical DataOpshttps://doi.org/10.1007/978-1-4842-5104-1_8

8. Organizing for DataOps

Harvinder Atwal¹ 

(1)

Isleworth, UK

 

Organizational structure has an enormous impact not only on output velocity but also on what teams produce and the quality of such. As anyone who has worked within a rigid hierarchical structure knows, the organizational chart often has more influence on what is or is not produced than any technology decision.

For example, with a traditional layered architecture, the simple addition of a new data source to a report requires coordination from every separate functional team responsible for a layer. Cutting vertically across layers requires source system owners, ETL developers, database architects, database ...