Approaching IT Projects with Data Quality in Mind

I co-authored a white paper at the end of 2006 with a simple goal: to talk directly to project managers about the process they go through when putting together a data intensive project. By “data intensive” project, I mean dealing with mergers and acquisitions data, CRM, ERP consolidation, Master Data Management, and any project where you have to move big data.

Project teams can be so focused on application features and functions that they sometimes miss the most important part. In the case of a merger, project teams must often deal with unknown data coming in from the merger that may require profiling at part of their project plan. In the case of a CRM system, companies are trying to consolidate whatever ad hoc system is in place and data from people who may care very little about data quality. In the case of master data management and data governance, the thought of sharing data across the enterprise brings to mind a need for a corporate standard for data. Data intensive projects may have different specific needs, but just remembering that you need to consider data in your project will get you far.

To achieve real success, companies need to plan a way to manage data as part of the project steps. If you don’t think about the data as part of the project preparation, blueprinting, implementation, rollout preparation, go live and maintenance, your project is vulnerable to failure. Most commonly, delay and failure is due to late-project realization that the data has problems. Knowing the data challenges you face early in the process is the key to success.

This white paper discusses the importance and ways to best involve business users in the project to ensure their needs are met. It covers ways to stay in scope on the project while considering the big picture and the going concern of data quality within your organization. Finally, it covers how to incorporate technology throughout a project to expedite data quality initiatives. The white paper is still available today for download. Click here and see "Data Quality Essentials: For Any Data-Intensive Project"

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