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- 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.
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