In this machine learning project, you will use the video clip of an IPL match played between CSK and RCB to forecast key performance indicators like the number of appearances of a brand logo, the frames, and the shortest and longest area percentage in the video.
One of the broadest uses of Snowflake is building a data warehouse platform or enhancing the existing data lake. It offers all sorts of services to build an efficient Data warehouse with ETL capability and support for various external data partners. Slowly Changing dimensions are a common database modeling technique used to capture data in a table and show how it changes over time. The slowly changing dimension of the warehouse dimension is said to rarely change. However, when they change, there should be a systematic approach to capturing that change. Examples of SCDs are customer and products information. This project explains how to build a Slowly Changing Dimension (SCD) using Snowflake’s Stream functionality and how to automate the process using Snowflake’s Task functionality.