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Implementing a Data Management Framework and Function

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About Course

This is Course 10 of the Program “Establishing a Data Management Function.”

 

This course is an advanced training course for data management professionals. This course has several objectives:

  • Share knowledge and assist in developing practical skills to implement a data management  function
  •  Explain the logical order of implementing various DM capabilities
  •  Assist in developing an implementation plan

After completing this course, you will be able to:

  • Prepare an implementation plan for your DM initiative and constituent capabilities
  • Create a knowledge graph of the artifacts of various DM capabilities
  • Implement a data management function

What Will You Learn?

  • An integrated approach to implementing multiple basic data management (DM) capabilities
  • Metamodel of linked DM artifacts
  • How to develop an implementation plan for your DM initiative and constituent capabilities
  • How to Implement the DM initiative and function
  • How to create a knowledge graph of the artifacts of various DM capabilities

Course Content

Introducing the “Data Management Star” Implementation Method
This section provides a high-level overview of the “Data Management Star” implementation method and its Step 3. This method forms the basis for the program “Establishing a Data Management Function.” In this section, we introduce Step 3 of this method, “Building a Data Management Framework.

  • Introducing the “Data Management Star” Implementation Method
    15:30

Mapping Processes and Roles
This section demonstrates the implementation of the data governance/management operating systems through the mapping of the chosen data management capabilities, related processes, deliverables, and roles. The design of the operating system we discussed in Course 4: “Designing a Data Governance Capability.”

Creating a Report Catalog
Any data-related initiative should start with an analysis of information output. Usually, information is delivered through reports and/or dashboards. This section demonstrates the method to document a report catalog and report flow.

Gathering Information Requirements
This section presents a method to gather business and information requirements.

Defining Critical Data
This section demonstrates the method to limit a data management initiative to a feasible scope by identifying critical reports and data elements.

Defining Metadata to Document
This section introduces the concept of metadata and explains an approach to choosing the required metadata to be documented.

Designing a Business Glossary
This section demonstrates various techniques to develop and maintain a business glossary.

Designing a Business Model
This section introduces several concepts of business architecture: “value stream,” “business capability,” and “business domain.” It also demonstrates the method to define business domains and link them to data models.

Documenting Business Processes
This section demonstrates the method to create a business process catalog.

Developing Data Models
This section introduces the concept of an enterprise data model. We discuss various existing approaches to data modeling. We also present templates for the documentation of business rules.

Documenting Data and Application Flows
This section provides the definitions of a data lifecycle, a data chain, and data lineage. It also demonstrates the method to document and maintain data and information technology assets.

Documenting Data Lineage
This section demonstrates a data lineage concept and a metamodel of data lineage in detail. We discuss the methods to implement data lineage.

Identifying Data Requirements
This section introduces the concepts of “data dictionary” and “(meta)data repository.” It also provides an example of the Template “Data Dictionary.”

Gathering Information and Data Quality Requirements
This section provides the definition of data quality dimension and presents 5 key data quality dimensions used in this course. It presents a template for gathering data quality requirements.

Profiling and Validating Data
This section discusses the content and objects of data profiling. It also introduces Methods to resolve data issues found as the result of data profiling.

Identifying and Solving Data Quality Issues
This section discusses the definition of a “data quality issue” and different types of data issues. It also demonstrates several approaches to remediating data issues.

Building Data Quality Checks
This section provides the definition of a “data quality check.” It also discusses the challenges associated with building data quality checks.

Student Ratings & Reviews

5.0
Total 2 Ratings
5
2 Ratings
4
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1
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RK
RENJITH K P
6 months ago
Excellent
AB
Amir Behboodi
2 years ago
This course helped me take a process-oriented approach to managing metadata and data quality. Using templates and guidelines aided me in organizing my thoughts and gaining a better perspective on documenting metadata and data quality activities.
Data Crossroads Academy