Data Lineage Fundamentals Learning Plan

DLIN1: Data Lineage Concepts

Course Curriculum

Introduction

• Goals and Objectives Per Target Audience
• Course Structure
• Syllabus

Part 1: An Introduction to a Data Lineage Concept

Section 1: The Role of Data Management in Creating Business Value

• Data Managements Role in the Business Value Chain Creation
• Data Management Definitions in Different Contexts
• Data Management and the Data Value Chain

Section 2: A Basic Definition of Data Linage

• Data Linage Defined
• Abstraction Levels
• Example 1: Solidatus
• Example 2: Manta

Section 3: Relationships Between Data Lineage and Other Similar Concepts

• Exercise 1: Analyze the Definitions of Concepts Comparable with Data Linage
• Template 1: Analysis of Data Lineage-Related Definitions
• Data Value Chain Defined
• Example: Complete Analysis of 6 Definitions
• Abstraction Levels

Section 4: The Relationships Between Data Lifecycle, Data Chain, and Data Lineage

• Data Lifecycle Defined
• The Data Lifecycle Model and a Company’s Business Model
• Data Chain Defined
• Data Chains and the Data Lifecycle
• Data Lineage Defined
• Data Lineage and Data Chains

Part 2: A Metamodel of Data Lineage

Section 5: Data and Metadata

• Data and Metadata Defined
• Metadata and Data Context
• Metadata Classifications
• Examples of Various Metadata Types
• Basic Definitions in Relation to Data
• Model and Metamodel Defined
• Data Lineage Metamodel and the Structure of Data Lineage

Section 7: A Metamodel of Data Lineage and It’s Key Components

• The Metamodel of Data Lineage Structure
  • Business Level
  • Conceptual/Semantic Level
  • Logical/Solution Level
  • Physical Level
• Template: Data Lineage Metamodel

Section 8: Data Lineage Types

• Data Lineage Classification
  • Subject
  • Layer
  • Direction
  • Documentation Method

Part 3: Data Lineage in the Context of Data Management

• Part 2: A Metamodel of Data Lineage

Section 9: Data Lineage and Data Management Capabilities

• Various Data Lineage Capabilities
• Exercise 2: Analyze the Existence of Key Data Management Capabilities in Your Company
• Template 2: Analysis of Key Data Management Capabilities Related to Data Lineage

Section 10: Data Lineage in the Context of Enterprise (Data) Architecture and Metadata Management

• Data Lineage and Enterprise (Data) Architecture: The Overlap
• Data Lineage is a Metadata Construct

Data Lineage Fundamentals Learning Plan – Progress Review

The 9 Steps to Successful Data Lineage Implementation

Primary Sources for the Learning Plan                               

DLIN2: 9-Step Method to Implement Data Lineage

Introduction

• Goals and Objectives Per Target Audience
• Structure
• Syllabus

Recap Course 1: Data Lineage Concepts

• The Metamodel of Data Lineage Structure
• Data Lineage Classification Assistance with Scope and Planning

Part 1: Outline a Data Lineage (DL) Initiative

Section 2: An Introduction to the 9-Step Method

• The 9 Steps to Successful Data Lineage Implementation

Section 3: Step 1 – Identify Key Business Drivers

• Various Internal and External Business Factors
• Step 1: Identifying Business Drivers
• Exercise 1: Document and Analyze the Criticality of Business Drivers for a Data Lineage Initiative
• Template 1: Document Business Drivers
• Template 2: Business Driver Analysis and Prioritization

Section 4: Step 2 – Identify Key Sponsors

• Data Lineage Stakeholder Defined
• Various Stakeholder Groups
• Exercise 2: Analyze Potential Sponsors/Key Stakeholders of Data Lineage Initiative
• Template 3: Stakeholder Analysis

Section 5: Step 3 – Scope a Data Lineage Initiative

• Six Factors in Identifying Scope of a Data Lineage Initiative
• Mapping Requirements to the Data Lineage Metamodel
• The Part of “Enterprise” to be Taken into the Scope of a Data Lineage Initiative
• The “Length” Factor
• The “Depth” Factor
• Critical Data Defined
• Exercise 3: Analyze the Scope of a Data Lineage Initiative
• Template 4: Analysis of the Scope of a Data Lineage Initiative

Section 6: Step 4 – Define Roles and Accountabilities

• Various Stakeholder Groups
• Data Management Roles of Various Types
• Involvement of Stakeholders

Section 7: Sep 5 – Prepare Data Lineage Requirements

• Requirements of Various Stakeholders
• Metadata Lineage Functional Requirements
• Data Lineage Should Have a Graphical Representation
• Data Lineage and Visible Metadata
• Drill-Up and Drill-Down Functionality
• Data Lineage Tracing Links
• Requirements for Horizontal and Vertical Data Lineage

Part 2: Plan the Implementation of a Data Lineage Initiative

Section 8: Step 6 – Choose and Approach and Method of Implementation

• Factors Influence Approach and Method to Documenting Data Lineage
• Advantages and Disadvantages of Choosing the Direction of Documentation
• Three Approaches to Manage a Data Lineage Initiative Exist

Section 9: Step 7 – Choose Appropriate Tooling

• Various Types of Data Lineage Solutions Exist
• Choosing a Data Lineage Tool for a Company

Section 10: Assess Risks and Develop Mitigation Actions

• Turning Risk Factors into Success Factors
• Exercise 3: Assess Risks and Develop Mitigation Actions for a Data Lineage Initiative
• Template 5: Define Key Risk Factors and Corresponding Mitigation Actions

Part 3: Perform the Implementation of the DL Initiative

• Data Lineage Documentation: Manually or Automatically
• Documentation Using the “Top-Down” or “Bottom-Up” Approach
• Automated Data Lineage Requirements

Section 10: Assess Risks and Develop Mitigation Actions

• Data Lineage Analytics Delivery
• Data Lineage Analytics Demonstrating Business Rules

Next Steps: Course 3 – Data Lineage Use Cases

• Data Lineage Fundamentals Learning Plan – Progress Review
• Data Lineage Use Cases

Primary Sources for the Learning Plan

DLIN3: Data Lineage Use Cases

Introductions

• Goals and Objectives Per Target Audience
• Structure
• Syllabus

Recap Course 2: 9-Step Method to Implement Data Lineage

• The 9 Steps to Successful Data Lineage Implementation
• Business Drivers Leading to Data Lineage Initiatives
• Various Stakeholder Needs and Expectations

Part 1: Needs of Various Stakeholders in Data Lineage

Section 2: Needs of a Company’s Management

• Needs and Benefits in Data Lineage-Related Initiatives
• Calculating Expected Gains, Required Investments, and Costs by Applying Management Accounting Techniques

Section 3: Needs of Business Data Stewards

• Businesspeople: Needs and Benefits in Data Lineage-Related Initiatives
• Various Data Lineage Stakeholders: Expectations from Data Lineage
• Data Value Lineage
• Business Data Stewards Requires Data Lineage at Several Abstraction Levels

Section 4: Needs of Data Management Stewards

• Needs and Benefits in Data Lineage-Related Initiatives
• Requiring Data Lineage at All Levels of Abstraction
• The Need to Perform Impact and Root-Cause Analysis at Various Abstraction Levels

Section 5: Needs of Technical (IT) Data Stewards

• Needs and Benefits in Data Lineage-Related Initiatives
• Requiring Data Lineage at the Logical and Physical Abstraction Levels
• The Need to Perform Impact and Root-Cause Analysis at the Physical Level

Part 2: Data Management Initiatives

Section 6: Metadata Management

• Metadata Management Defined
• Data Lineage Enables Metadata Management

Section 7: Critical Data

• Critical Data Defined
• Five Different Types of Critical Data Elements Recognized and Documented at Different Abstraction Levels Along Data Chains

Section 8: Data Quality

• Analyzing Data Quality Issues and Building Data Checks by Performing Root-Cause Analysis
• Analyzing Changes in Data Chains by Performing Impact Analysis

Section 9: Reference and Master Data Initiatives

• Reference and Master Data Defined
• Identifying the Systems of Records and References

Section 10: Devops and Migration Projects

• Removing Data Redundancy and Optimizing Data Chains

Section 11: Implementation of a Data Management Framework

Data Lineage Fundamentals Learning Plan – Progress Review

Primary Sources for the Learning Plan