DataOps is emerging as a new practice for working with data, bringing new data governance challenges with it. This paper outlines a new data governance definition, an accompanying set of DataOps principles and reference architecture for real-time apps.
The architecture outlined has enabled Swiss financial services provider Viseca to comply with stringent regulations in a dynamic market; but it also fast-tracked their Apache Kafka project to production, reducing time-to-market of streaming apps by 10x.
What is data governance today, and why is it changing? How can it impact your data projects?
How can you deliver an enterprise-wide real-time data platform service?
What practical techniques can you use to build data access models with technologies such as Apache Kafka?