BI Axioms

A few months ago, I did an assessment for a large company that was advised by an undisclosed source that they should use their Dynamics Financials and Operations (F&O) system as a data warehouse. Recently, I came across a similar wish to use SAP as a data warehouse. I understand that people want to do more with less and shortcuts are tempting. But ERP systems can’t fulfill this purpose, and neither can other systems of record. True, these systems might have analytical features, but these features typically deliver only operational reporting. Operational reporting has a narrow view concerned with “now”, such as a report that shows customers with outstanding balances as of today. By contrast, BI is mostly concerned with historical and trend analysis.

In math, axioms are statements that are assumed to be correct without a proof. We need BI axioms and the list can start like this:

• Every mid to large company shall have a centralized data repository for consolidating trusted data that is optimized for reporting. The necessary for such a repository is in a direct proportion with the number of the data sources that must be integrated (that number will increase over time) and the complexity of the data transformation. The centralized data repository is commonly referred to as a data warehouse.
• Dimensional modeling shall be the methodology to design the data warehouse schema. I know it’s tempting to declare your ODS as a data warehouse, but highly normalized schemas are not suitable for reporting.
• If you’re after a single version of the truth, you shall have an organizational semantic layer.
• ERP systems are not a replacement for a data warehouse. Neither are data lakes and Big Data.
• You shall have both organizational and self-service BI, and they should complement each other. If you lean too much toward organization BI, you’ll get a backlog of requirements. If you lean too much toward self-service BI, you’ll end up with fragmented “spreadmarts”, which is where you probably started.
• Most of the BI effort should go toward organizational BI to integrate data, improve data quality, and centralize business calculations. Tools come and go but this effort shall endure.
• Agile and managed self-service BI shall fill in the gaps. It should provide a feedback loop to extend organizational BI with data that the entire organization can benefit from.