Snowflake for Data Products: Data Monetisation & Experience | Part 2

This piece is part of an ongoing series. If you’re here for the first time, you can refer to part 1 to get more context on:Motivation for data products/Why repurpose existing stack?: Cost savings, Monetisation, ExperienceHow Snowflake is realigned to support Data Products?Establishing cost efficiencies for Snowflake as a result of Data ProductsA step-wise breakdown with some YAML & SQL samples for Snowflake connectivity and Data Product ActivationAccess Part 1 ⬇️Now, let’s dive into the two other forks of business ⬇️Monetisation & Experience of Data CitizensTo understand how Snowflake & Data Products combined can achieve an impact on revenue, we need to understand what exactly data monetisation means.Here’s a direct excerpt from The Data Strategy Show hosted by Samir Sharma, CEO at datazuum & featuring Saurabh Gupta, Chief Strategy Officer at Modern. 6-7 years ago, everybody was talking about monetisation, trying to get their data assets to be valued and put on the balanced sheet. But monetisation has a lot of different criteria for different people.