Repost Linkedin : https://www.linkedin.com/posts/yacine-bekka_data-quality-management-activity-7018491937175306241-AtNb?utm_source=share&utm_medium=member_desktop
Let me explain the process I use with my clients to manage their data quality 👇
📜 Define initial standards for monitoring hashtag#dataquality
- Document business rules and derive associated data quality indicators
- Define monitoring methodology (frequency, queries used, etc.)
👀 Start monitoring
- Conduct initial data quality monitoring based on the newly defined standards
- Identify current data quality issues (non-compliance with one or more business rules)
🧠 Investigate root causes and effort for data correction
- Analyze the data quality issues to understand what the root cause(s) are and what effort is required to correct the data affected by them
🗣️ Communicate findings with the business and establish priorities
- Share your findings with business stakeholders and determine the criticality of the issue based on business impact
- Determine priority based on cost (effort required to correct the data and root cause) and benefit (business impact)
🔧 Correct data and root cause(s)
- Ideally, data correction should be done in the source system
- Depending on the context (legacy application that cannot be updated, etc.), sometimes the correction needs to be done on the fly between the source and the data warehouse
🔄 Iterate
- Ensure that data consumers have the opportunity to raise issues not covered by the process
- The quality standard should be updated after new business/quality rules are created or discovered