1. Definition of Data Quality.
2. Trends in Data Quality management
3. Problems Encountered with Data Quality
4. Benefits of Data Quality
5. Data Quality Management
   1. Data Profiling
      1. What is Data Profiling?
      2. Why is Data Profiling Important?
         1. Illustrate with example
      3. When is Data Profiling performed?
         1. Requirements Gathering/ Data Analysis
         2. Data Quality Assessment
      4. Different Types of Data Profiling
         1. Column Analysis
         2. Business Rule Analysis
         3. Correlation Analysis
         4. Schema Analysis
         5. Redundancy Analysis
      5. Overview of Talend Open Profiler
         1. Provide Website Link
      6. Demonstration of Data Profiling using Talend Open Profiler.
      7. Q&A Session
      8. Recommended Resources
         1. Books
            1. Data Quality - The Accuracy Dimension
            2. Data Quality Assessment by Arkady Maydanchik
         2. Websites
            1. www.dataqualitypro.com
            2. www.talend.com
         3. Blogs
   2. Data Monitoring
   3. Data Cleansing and supporting activities.