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Data quality is a significant issue facing many organizations. Despite the costs and headaches associated with having poor data, most organizations struggle to define and implement a strategy for effectively improving data quality. Data quality costs organizations time, effort and money.
There are five types of interrelated data quality issues:
- Data duplication
- Stale data
- Incomplete data
- Invalid data
- Data conflicts
This video will provide an overview of what data quality is, how it negatively impacts the organization, and steps that can be taken by the business and IT in order to mitigate data quality risks and to improve quality.
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