We have discussed previously the importance of data quality to business intelligence. I’d like to go a bit deeper on that topic here in this post.
It is plainly obvious that your business intelligence will only be as good as the quality of your data; this, in turn, means the quality of business answers derived from your BI logic are also dependent on the data’s quality. It’s the cliché garbage in-garbage out scenario.
For the sake of a quick review, let’s recap several important reasons to implement a data quality strategy, including:
- The ability to trust data
- Accurate and timely information
While we have discussed data quality as it pertains to business intelligence success, we have not touched on the tight interaction and necessity of a strong master data management (MDM) solution. A strong MDM solution is designed to consolidate, enrich, synchronize and cleanse data across all applications of the enterprise.
Imagine a distinct CRM solution, a distinct order management solution, a distinct inventory solution, a distinct billing and accounts receivable solution. All of these products have at least one key and critical element in common: the customer. If there is no mechanism in place to control the entry, deletion or editing of customers across these solutions, the business intelligence implications are absolutely perilous.
Take, for example, the simple customer ID. If it is not the same across all of these distinct-but-interfaced solutions, the reporting and ability to trust information will be seriously compromised. Unfortunately it is not an uncommon scenario in which business units within the same organization describe products, customers, vendors etc. with different descriptors or IDs. These organizations end up with data quality issues
or some combination of transformation tables designed to sync up the different naming and identification conventions.
It can be a nasty mess, full-stop.
A MDM solution with a single point of entry and control reduces the risk of uncontrolled and unmanageable differences in master data. When data is cleansed upon entry, the data has a significantly better chance of remaining clean and synchronized across the enterprise, which results in better business intelligence. MDM solutions hold the single source of the truth across key business dimensions such as customers, vendors, products and locations.
As your business intelligence strategy matures, investigate the potential need for and implementation of a MDM solution to better control the quality of the data and therefore the quality of your business intelligence solution. I encourage you to learn more about Oracle’s MDM solution, and if you have further questions or want to know more about this topic, email me. I’m happy to help.
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