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Four common data integration issues and challenges
Embarking on a data integration project? Make sure you know common data integration issues and challenges before beginning your next integration implementation.
What are some important data integration issues that companies typically overlook?
The most overlooked
data integration issues and challenges that we come across include:
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Step 2 of 2:
- Using a data profiling tool to analyze and measure data quality of both source or target environment data prior to developing the integration logic.
- Establishing data acceptance criteria for an individual application system. Perfect data isn't practical; the focus should be "good enough." And the business stakeholders involved in an integration project should be able to identify usage scenarios that reflect what "good enough" looks like.
- Including a data quality/accuracy review step as part of the design review step in an overall development project.
- Establishing standard load and export interfaces for systems that provide data and take it on board on a regular basis. Most integration development follows a one-off approach even when it's common for some systems to on-board data from new systems on a regular basis.
This was last published in February 2010
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