There are several general rules in designing and implementing BI/DW projects to ensure the successful and quality of the projects. I am trying to consolidate some of those important best practices from what I have learned and experienced.
In this series, I will focus on those practices related to my role, experiences and exposure. So, it doesn't a complete list of best practices in the BI/DW industry.
The list of BI best practices
- Best Practice #1 - Principles
- Best Practice #2 - Use common business languages
- Best Practice #3 - Understand the business processes
- Best Practice #4 - Organization wide participation to ensure data quality
- Best Practice #5 - Consolidate entities while keep correct grain
- Best Practice #6 - Denormalize the data in the user access layer
- Best Practice #7 - Atomic grain base fact table
- Best Practice #8 - Use Surrogate key
- Best Practice #9 - Contain date dimension in all fact tables
- Best Practice #10 - Handle unknown and null
- Best Practice #11 - Decouple with source systems
- Best Practice #12 - Manage data integrity
- Best Practice #13 - Keep measures additive if possible
- Best Practice #14 - Flexible and rerunable ETL processes
- Best Practice #15 - Be careful to be pilot project
- Best Practice #16 - Start small, release in batches
- Best Practice #17 - Think carefully before violating best practices
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