We live in a world of metaphors, there are new terms and metaphors which are heard everyday, with that it causes a lot of confusion, pressure and also some amount of chaos. It is important to filter out the noise and focus on what are needs of the business, customers/stakeholders. There are continuous attempts to streamline data projects, the reason being there is lot of unwanted costs, project delays and failed implementations. The whole purpose of data projects should be focused on value add for business or improving customer experiences and better integration of systems. In the Agile world, we have heard of Devops as a way to provide Continuous integration and Continuous deployment, similarly there emerged DataOps. What is DataOps:
Through firsthand experience working with data across organizations, tools, and industries we have uncovered a better way to develop and deliver analytics that we call DataOps.
Handle the 3 D's: They are Technical Debt, Data Debt and Brain Debt. I would like to thank Data Engineer/Cloud Consultant Bobby Allen for sharing this concept with me. Extremely important to handle this while taking up data projects.
Ability to build and dispose Environments - Data Projects rely heavily on data, the ability to build environments for data projects and quickly dismantle them for newer projects is the key.
It is very important to implement DataOps in terms of what is the value add for the business and how data will improve Customer Experience.
There tools that implement Dataops, some of the tools already in the market are: Atlan, Amazon Aethana.