Create general training guide on how to replicate business logic from systems
Background
The Data team pulls in data from multiple systems at GitLab. Therefore, original data models pulled into the Data team data via extraction into the Data warehouse lacks the context of how system owners have programmed the rules engine or transformed business logic into the system to collect data in a certain way.
Consequently, it is important for anyone analyzing data to understand how data collection in a system occurs defines how the data will be processed, modeled, and viewed with it's data caveats in other systems, such as in the Data warehouse. It will also help to navigate data analysis by giving the user confidence that they understand how data is surfaced in the original system and can be resurfaced in the Data Team Business Intelligence tool - Sisense.
Solution
This issue focuses on creating a general training guide that will enable anyone with a strong interest in Data and a background in intermediate SQL to explore a new system data set and create reports that replicate the system user interface dashboards or charts in the Data team data warehouse (Snowflake/Sisense).