Many organizations with the hope of becoming more data-driven ask the question: self-service analytics, or data science operationalization - which will get me where I need to be? And the answer is: you need both together.
The fact is, it’s the interplay and balance between operationalization (o16n) and self-service analytics (SSA) initiatives that makes a successful data-powered company that executes on all projects to its fullest potential. While at first glance the two appear to be completely different (maybe even contradictory), it’s precisely because they differ in value, scale, and more that they round out a complete data strategy.
This video takes a look at how to implement a complete strategy for both, pitfalls to avoid along the way, and case studies of large enterprises who have successfully implemented the two.