Your customers live in an “Amazon World”: they expect data and analytic insights, delivered in a neat package as quickly as possible. But as a leader of data and analytic teams, you know that in order to bring those insights together you have to aggregate multiple people across various teams and business units — all of whom are leveraging different software tools. DataOps improves collaboration and offers a solution to these challenges by providing a technical platform that aligns people, processes and tools for improved and increased analytic outcomes.
The biggest challenge in data and analytics is that projects continue to fail. In fact, Gartner estimates that despite increased investments in talent and tooling, as many as fifty to eighty percent of data and analytics projects fail every year. This fundamentally comes down to a people and process problem, which is exactly what DataOps is designed to address.
- Why data and analytics projects fail
- Best practices for implementing DataOps
- How to measure DataOps success