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Data quality is key to realizing value from any investment in data management, mining and analytic technologies. Data hygiene should be core to an organization's strategy, and it has to be conducted on a regular basis.

Inaccurate data can have a detrimental effect on the business and will decreases productivity in the organization. If data quality issues are not addressed, insights from data analysis will not be accurate. Whether bad data causes your organization to lose revenue, damages your brand, reduces your competitive edge, or simply results in bad decision-making, the costs are significant.

See how 17 data management technology vendors stack up when comparing performance across this following set of the most significant use cases for data quality tools:

  • Big Data and analytics
  • Data Integration
  • Data Migration
  • Information Governance Initiatives
  • Master Data Management
  • Operational/Transactional Data Quality

 

Critical Capabilities for Data Quality Tools

 

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