What is Reinforcement Learning (RL)? Definition, Algorithms, Examples
How to build reliable data products your company will actually use?
It’s time to treat data like a product, not an afterthought. A new paradigm has emerged among forward-thinking data teams: treat your data like a product.
This may sound easy in theory, but it’s far from it! Product development processes have become incredibly sophisticated, with resources dedicated to reliability, adoption, feature roadmaps, and more.
While challenging, data products also present an incredible opportunity for data teams to increase trust, measure value, and improve capacity.
In this guide, we’ll take you beyond the buzz and into the best practices deployed by some of today’s leading data professionals, covering:
- Creating SLAs and Assigning ownership
- Documentation, discovery, and self-service
- Governance and compliance
- Developing data contracts and certifying data sets
- Assessing and demonstrating value with KPIs
- DataOps and agile methodologies
Our guide will take you beyond the buzz and into the best practices deployed by some of today’s leading data professionals. Get your free copy today!