Snowflake SnoPITs for Bi Temporal Finance Data

In this webinar, we address how to effectively deal with multi-temporal financial data in the Data Vault on Snowflake.
Banks, insurance businesses, and other financial institutions often have to grapple with multiple timelines in their data. This challenge makes the storage and evaluation of such data challenging, expensive, and slow.
In this webinar, we combine technical and business perspectives by using automation to efficiently generate implementations on Snowflake from a business model.
In the first part, Patrick Cuba introduces the concept of 'SnoPITs' to access the right version of information in a very efficient way over time. Petr Beles will present that applying these kinds of patterns can be simple to achieve when data models and automation are used to generate them.
Together, they will show how such an implementation on Snowflake differs in terms of compute and I/O for queries compared to an approach without this kind of optimization.