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Class Description


 
Data Quality and Governance

Data is the life blood of all organizations. Information Technology (IT) managers and individual contributors are the guardians of this data. As a result, IT must understand how data is collected, stored, distributed, used, and in regard to this class, managed.

To that end, we will discuss the data quality requirements for different data types, the business, IT and vendor practices that help create bad data, processes to help identify bad data, and the management practices and data governance needed to help facilitate the distribution of quality information.

Class Topics include:
  • Data Quality Requirements
    • How different types of data require different levels of quality
  • Causes of Bad Data
    • Data problems caused by vendors
    • Data problems caused by IT architectures
  • Identifying Bad Data
    • Ways to monitor and identify bad data
    • Data health check philosophy and practices
  • Data Friendly Topologies
    • Internal and external data-friendly topologies
    • Modifying existing data flows and topologies
  • Data Governance and Management
    • Data governance and Data Governance Group (DGG) definitions
    • Responsibilities, location, level, and structure
    • Challenges of justifying a DGG
  • Effect of Cloud Computing on Data Management
    • Data Definition and Data Movement Issues
    • Inter-Cloud Transactions Issues
    • Data Warehousing and Analytics Issues
  • Effect of Big Data on Data Management
    • Information Governance
    • Operational, Administrative and Business Metadata
Key Take-A-Ways:
  • Definitions of key quality data types and considerations
  • Understanding of data governance political and financial dynamics
  • Data Governance Group vision, mission, and organizational structure

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