Month 47: Data Quality and Cleansing
Week 1: Introduction to Data Quality
- Day 1: Overview of Data Quality
- Day 2: Understanding Data Quality Dimensions
- Day 3: The Impact of Poor Data Quality
- Day 4: The Role of Data Governance in Data Quality
- Day 5: Data Quality Assessment Techniques
Week 2: Techniques for Data Cleansing
- Day 1: Introduction to Data Cleansing
- Day 2: Data Cleansing Techniques: De-duplication
- Day 3: Data Cleansing Techniques: Standardization
- Day 4: Data Cleansing Techniques: Validation
- Day 5: Data Cleansing Techniques: Enrichment
Week 3: Tools and Techniques for Data Quality and Cleansing
- Day 1: Overview of Data Quality and Cleansing Tools
- Day 2: Using Python for Data Cleansing
- Day 3: Using R for Data Cleansing
- Day 4: Using SQL for Data Cleansing
- Day 5: Using Data Quality Tools: Trifacta, Talend, etc.
Week 4: Implementing a Data Quality Framework
- Day 1: Building a Data Quality Strategy
- Day 2: Implementing Data Quality Controls
- Day 3: Monitoring and Reporting on Data Quality
- Day 4: Building a Culture of Data Quality
- Day 5: Case Study: Implementing a Data Quality Framework
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