Every once in awhile companies select data & analytics products, such cloud data platforms, ML/AI tools, and data catalogs. Organizations often bet hundreds of thousands, if not millions, of dollars on these decisions. And staff have to interact with these tools and platforms for years, if not decades. Even tools purchased for a single department have long lifespans. So it's imperative that organizations make the right choices.

Given the stakes, data leaders need a rigorous methodology for evaluating and selecting data & analytics products.

Unfortunately, some data leaders rush the process and pay the consequences later when they discover the tools fail to perform as expected, they lack critical integrations, or teams refuse to use them.

In this webinar, Eckerson Group consultants step through the methodology and templates they use with clients to evaluate and select products. They discuss who should be involved in the process, how to avoid common pitfalls, and how to ensure adoption.

You Will Learn:

● When a formal product evaluation is required and when it's not.

● Who should participate in a product evaluation, internally and externally.

● Pitfalls to avoid when evaluating and selecting products.

● The best way to compile evaluation criteria and score products.

● Whether and how to conduct a proof of concept.

● How to implement a product to ensure adoption.