5.00
(2 Ratings)
Implementing a Data Management Framework and Function
Categories: Enterprise Data Governance
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.
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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.”
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Mapping Processes and Roles
04:13
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.
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Creating a Report Catalog
07:52
Gathering Information Requirements
This section presents a method to gather business and information requirements.
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Gathering Information Requirements
11:18
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.
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Defining Critical Data
15:40
Defining Metadata to Document
This section introduces the concept of metadata and explains an approach to choosing the required metadata to be documented.
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Defining Metadata to Document
10:48
Designing a Business Glossary
This section demonstrates various techniques to develop and maintain a business glossary.
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Draft Lesson
10:07
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.
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Designing a Business Model
17:46
Documenting Business Processes
This section demonstrates the method to create a business process catalog.
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Documenting Business Processes
06:19
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.
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Developing Data Models
12:56
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.
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Documenting Data and Application Flows
10:36
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.
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Documenting Data Lineage
14:56
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.”
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Identifying Data Requirements
10:11
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.
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Gathering Information and Data Quality Requirements
08:13
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.
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Profiling and Validating Data
07:32
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.
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Identifying and Solving Data Quality Issues
08:35
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.
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Building Data Quality Checks
07:58
Student Ratings & Reviews
5.0
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Excellent
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.
