A data integrity parable

“A CFO and a CIO walk into a bar …”

… and start to discuss their firm’s upcoming financial reporting upgrade.

We have picked world’s best ERP package. We have purchased top of the line servers. Our SAN has been tuned by the vendor for optimal performance. The entity-relationship model for our data mart came straight out of industry best practices.

I hear what you are saying … but how can I be sure my business partners and financial analysts will be able to find the insight that we need to grow the business?

We are pulling in data from every operational system … it has to be in there somewhere.

In there somewhere! … I believe that. Somewhere we can find? … that part makes me skeptical. Your design team walked me through the data model … I saw cryptic names that may represent our accounts and products and channels and regions … but if we just drag-and-drop the classification schemes we have now into the new environment, we have a more expensive box churning the same old clumps of data?

read on...

Many implementations fail to achieve their potential. Not because the technology comes up short but because the reference data plugged into it is not up to the task.

Reference data is the foundation of every business ecosystem. It defines the frame of reference used to organize your business. Ultimately, it determines how well your organization can fulfill reporting and analysis needs.

Poorly designed reference data increases risks and costs for your reporting environment:

• queries and reports will run poorly even in a well-tuned technical environment
• reporting building and maintenance will be more difficult and more expensive
• tracing data lineage to establish audit trails will be more complex
• data governance is unsustainable due to ill-defined business rules
• data reconciliation across the technical landscape may not be practical (or even possible)
• data integrity suffers from ambiguous classifications

The relatively small investment to create an integrated reference taxonomy where reporting dimensions are clearly defined, populated with a rationalized set of members, and aligned with the analytical and business reporting requirements can pay significant dividends.

How you design the reference content is just as important as how you design the technical infrastructure.

Designing the reference content requires

• business perspective into how data should be classified to best meet reporting and analysis needs
• technical perspective into how reference data is consumed by the tools and how content moves among the various technical components
• expertise in optimizing reference taxonomies

den Karte brings those skills to clients preparing for business transformation and systems implementation activities.