Maximizing Your Data Quality Tool Investment

by Jodee Hale-Schmid

August 11, 2010

Authored by: Jim Whyte, Director of Solutions Consulting, Utopia, Inc.


In the data management space, a data quality tool is a must have for a sustainable enterprise information management program.

Depending on your software choice, it is a versatile tool to have deployed as it can address a number of your basic data management capability needs: extracting data, profiling, standardizing, enrichment, matching and merging and loading data across a variety of hardware and database platforms, file formats, purchased software and proprietary applications.

As important as it is to have utility tools that provide the above technical capabilities it is how those capabilities can be deployed that really provides the business value to the company.

The obvious use for a data quality toolset is in the area of data migration; either the one-time legacy system to the new target application ETL process, or for on-going periodic data migration as in the case of ERP to data warehouse data transfer.

Other options for this toolset is to leverage the data transform and validation routines you created for your one-time data migration process and redirect those jobs to run against your new strategic source system. Either passively, after data entry, to monitor your data quality and adherence to business and validation rules or real-time at the point of data capture to automate enforcement of data standards and ensure data integrity.

A surgical use of the data quality tool is managing your “denied party” requirements. Typically, each country maintains a list of individuals and companies that are to be blocked from trade and commerce with legal entities within a given country. Data quality tools can be leveraged to access these “denied party” lists and compare to your customer and vendor files to ensure your compliance.

One final suggestion with regard to the leverage and reuse of your data quality tool suite is in the area of mergers and acquisitions. Think your “one-time” data migration process now on “wash, rinse and repeat” mode. Any organization that is active in the M&A space should really be leveraging data quality tools. Data migration is usually one of the longer tracks to plan for in an M&A project.

  • A clean team can use the tools to evaluate your acquisition target and assess the data quality and provide estimates for the time required to convert and transform the data to your target applications using your existing business rules as its baseline.

  • The clean team can also assess the number of unique customers and products you will be acquiring and the overlap you will have with their existing suppliers – all data points to be assessed during the due diligence process.
  • Furthermore, having a standard data migration process in place allows you to stream line the data conversion process and enables you to take data off the critical path during the transition phase. There is no substitute for front-end data assessment required to map your acquisition data structures (context and structure) to your target applications. But 80% of your transformation logic and 100% of your data load routines are reusable which can provide significant reductions in cost and time to deliver.



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