A Day in the Life of a DataOps Engineer
A DataOps implementation project consists of three steps. First, you must understand the existing challenges of the data team, including the data architecture and end-to-end toolchain. Second, you must establish a definition of “done.” In DataOps, the definition of...
DataOps Lowers The Cost Of Asking Analytic Questions
How Predictive and Prescriptive Analytics Improve the Call Center Experience
Why Enterprise AI Needs Human Intervention
What is a DataOps Engineer?
A DataOps Engineer owns the assembly line that's used to build a data and analytic product. Data operations (or data production) is a series of pipeline procedures that take raw data, progress through a series of processing and transformation steps, and output...
Everything You Need to Know About DataOps Solutions
Start DataOps Today with ‘Lean DataOps’
Data organizations don’t always have the budget or schedule required for DataOps when conceived as a top-to-bottom, enterprise-wide transformational change. An essential part of the DataOps methodology is Agile Development, which breaks development into incremental...
DataOps is the Factory that Supports Your Data Mesh
Below is our final post (5 of 5) on combining data mesh with DataOps to foster innovation while addressing the challenges of a data mesh decentralized architecture. We see a DataOps process hub like the DataKitchen Platform playing a central supporting role in...
What Should Enterprises Do to Offset Future Technology Disruption?
