We are in the process of implementing an ERP solution (SAP). We would like to formulate a data management framework for the project and company. Any assistance and guidelines will be appreciated.
Larissa Moss’ Answer: ERP implementations are prime opportunities to improve the quality of your operational data. Several years ago, too many companies rushed through their ERP conversions (largely driven by the Y2K deadline) and propagated their source data quality problems into their new ERP environment. Don't make that mistake! Before embarking on the source-to-target mapping activities, perform some source data archeology and do some data profiling. Look for the following data domain and data integrity violations:
Use a data profiling tool or write short programs to examine the data values in your source files and databases, and determine the data quality problems. How many records have bad data? How critical are those data elements to your organization? How clean does your business community require the data to be? Be sure to talk to downstream information consumers and not just the data originators about their expectations of data quality. Then classify your source data elements into three categories: critical data (must be of pristine quality), important but not critical data (should have less than x percent bad data values, x to be determined by your business community), insignificant data (used for informational purposes and can contain wrong values without having an impact on the organization). Be sure to cleanse all of the critical data and as much of the important data as you can before or during your ERP conversion. Monitor the data quality in your ERP databases on an ongoing basis by setting up automated data profiling jobs to run monthly or quarterly audits. Establish a procedure to continuously correct dirty data before it has a chance to contaminate downstream decision support applications.
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