Data Governance

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Common problems with many decision support systems are the amount of variation, redundancy and overlap that exists within the data models and business logic used across multiple analytical applications. These problems can delay critical decisions and disrupt IT operations while users struggle to verify the truth in data.
Having data is one thing, having “good data” is another.
- QlikView
Data Governance can be considered ambiguous as it has an emerging definition – it can be simply defined as the exercise of authority for data related matters. It ensures that important information assets are formally managed throughout the enterprise and can be trusted to provide effective decisions.
Some of the goals of applying Data Governance practices include:
  • Increasing consistency
  • Reducing redundancy
  • Improving regulatory compliance
  • Improving security
  • Introducing best practices and repeatable processes
  • Encouraging reuse
  • Conforming column definitions across all applications
Data Cleansing and Governance

Data Governance using QlikView