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Data Quality Management


 

Valid data lies at the heart of the strategic, tactical and operational steering of every organization. Companies can only unlock the full economic potential of their data if the master data is well managed and provided in high quality. 

Data Quality Assessment
Data Cleansing
Data Mining


  ► Data Quality Assessment – Identify data issues and data quality rules
- Review and assess source data quality
- Understand data issues
- Review profile result
- Verify Completeness and consistency
- Verify validity and conformance to standards

  ► Data Cleansing – Cleanse and standardize Data
- Define data cleansing process specification
- Prioritize data quality levels
- Capture data quality rules to metadata repository
- Apply data quality rules to data in a data cleansing area
- Manage exceptions

  ► Data Mining – Review and analyze data
- Develop data metrics for measurement
- Monitor data quality
- Preform source system and enterprise data audit
- Gain insights about metadata
- Knowledge deployment