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A complete data quality solution

When you decide to take on a data integration project, it will require a lot of advanced planning, work, time and resources. Without a deep understanding of what the project's requirements, it's unlikely that you will complete the integration on time and on budget. Yesterday, Rishi Patel, Strategic Account Manager at Experian Data Quality and Michael Ott, Senior Vice President at Innovative Systems, Inc., an Experian Data Quality partner, presented a webinar, “De-risking data integration projects.” The webinar focused on four major topics: the historical challenges of data integration projects, how current environments introduce additional complexity, an advanced methodology for overcoming data integration challenges, and a checklist to ensure that your project stays on track for success.

1. Historical challenges of data integration projects– Did you know that 80 percent of data integration projects fail? Organizations historically have had challenges with data for a number of reasons. The main issues are a lack of understanding data, difficulty estimating time, cost, and resources associated with integration projects, as well as the volume of rework that will likely to be needed because of poor documentation or systems that don’t meet business user specifications. Good news: there are advanced methodologies for dealing with these historical problems!

2. Current environments introduce additional complexity – The complexity of today’s ecosystems makes it particularly challenging to support business initiatives that involve data. This is due in part to the volume of data that organizations are dealing with but also, the lack of control they have over their data from other systems or third parties. The need for a solution that can easily handle all of these data types and formats is critical.

3. An advanced methodology for overcoming data integration challenges – Business users need to be closely aligned with analysts and IT during data integration projects. Enabling business users a seat at the table from the beginning empowers them to give feedback early and often in the project, and can sufficiently decrease the amount of rework and will increase your data integration project’s success.

4. A checklist to keep your project on track – Data integration projects have a lot of steps, requirements and dependencies. Use this checklist as a guide for planning and tracking project milestones.

  • Pre-integration planning
  • Project initiation
  • Landscape analysis
  • Solution design
  • Build and test
  • Execute and validate
  • Hand over ownership

You can watch the full webinar recording below, or for more information on how Experian Data Quality can help streamline your data integration project, check out Experian Pandora.