Introduction to Data Governance and Assessing Data Maturity

Course 1292

  • Duration: 3 days
  • Language: English
  • Level: Intermediate

This Data Governance and Maturity Training helps you understand Data Governance and assess your Data Maturity. It uses the IEC/ISO 38505 governance of data standards, written for organizations that want to develop and implement a data strategy. For example, this strategy may be part of a plan to deliver new services or products to their customers.

Data Governance and Maturity Training Delivery Methods

  • In-Person

  • Online

Data Governance and Maturity Training Information

In this course, you will:

  • Learn the different Data Terminology: OLTP and OLAP, Dashboards, and Scorecards.
  • Understand what data is and the history of data.
  • Learn about the different data maturity levels.
  • Understand how to make decisions with data, report on the data, and distribute the data.
  • Understand when to dispose of data and why.

Training Prerequisites

  • Attendees should have a basic understanding of what data is and the function of data analysis.
  • You can gain this from attending course Learning Tree course 1290, Introduction to Data Analytics.

Certification Information

Learning Tree End of Course Exam included

Data Governance and Maturity Training Outline

What Is Data?
Health and Census Data
Traditional and Modern Data-Heavy Industries
Data Quality Disasters
How Good and Bad Data Impacts Your Business
Why Poor-Quality Data Exists
Data and the Digital Revolution
Five Key Drivers for Data Awareness
Causes of Poor Data Quality
Components of a Data Solution
Data Products: Terminology
Data Products: OLTP and OLAP
Data Products: Dashboards and Scorecards
Data Products: Extract, Transform, Load, and Reporting Tools
“Big” Data
Data and Digital

Data Governance Or Data Management?
Data Governance Standards
Other Definitions of Data Governance
Data Governance Responsibilities
Data Management
ISO Standards In This Course
ISO/DIS 37000 Wheel: The Centrality Of Governance
ISO/DIS 37000*:
Guidance for the Governance of Organizations
ISO/IEC 38500:2015
Governance of IT for The Organization
Data Governance
The Definitions and Focus of Data Governance
Other Definitions of Data Governance
Six Use Cases for Data Governance
Data Governance: Areas of Focus
Who Manages Data Governance?

Trust Issues
Impact On Directors
Opportunities For Data-Driven Business
The Risk of Unintended Outcomes
Regulation Of Data
Maturity Assessment: Creating the Vision
Data Maturity Levels
Level 1: Data Aware
Level 2: Data Capable
Level 3: Data Adept
Level 4: Data Informed
Level 5: Data Pioneer
Discussion Point: Driving Data Initiatives Forward
What Are Business Drivers?
Top-Down Data Analysis
Enterprise Information Architecture
Designing Standardized Business Metadata
Bottom-Up Source Data Analysis
Source Data Selection
Data Selection Issues
Extract, Transform, and Load (ETL)
Examples: Specifying ETL Rules
Data Technologies
Enabling Technologies That Generate Data
Moving Data to a Data Warehouse
Developing the Data Warehouse
OLAP Terminology
Value of OLAP
Identifying Enterprise Systems and Data
How Is Enterprise Data Stored?
Unstructured Data
Technical Infrastructure
Issues: Structured and Unstructured Data

Principles & Components of Data Governance
The Principles of Data Governance
Components of Data Governance
The Data Governance Paradox
The Data Governance Paradox: The Hidden Data Factory
Barriers to Data Governance
When Data Governance Fails
Setting Governance Goals and Objectives
Creating Your Data Governance Vision

Your Key Data Challenges
Data Management Metrics
Business Culture
Effective Business Communication
Selling Data Governance
Business Culture Change and Data Governance
Creating a Cultural Change Plan
Communications Strategies for a Cultural Change Plan
Using a Motivation Model
Using a Motivation Model
Tools & Technology
Building a Data Governance Business Case
What Are Business Drivers?
Building a Data Governance Business Case:
Costs and Benefits
Building a Data Governance Business Case:
Implementation Plan
Five Data Governance Models
Pros & Cons of Each Model
Using The Right Model for Your Organization

Data Governance Framework
Data Governance Framework Examples: DGI
Data Governance Framework Examples: McKinsey
Data Governance Framework: Overview
The Data Governance Framework: Vision
The Data Governance Framework: Strategy
The Data Governance Framework: Organization & People
Implementing a Data Governance Framework
What Does a Data Governance Framework Provide?
The Benefits of a Data Governance Framework
DGF Deliverables & Actions Checklist
Data Governance Framework

The Data Governance Roadmap
Data Governance Capability Mapping
The Data Governance Roadmap Checklist
Hints & Tips for Developing Roadmaps
Organizing Practical Data Management
Identifying and Designing Data Management Processes
Data Ownership & Stewardship
What are Stakeholders?
Types of Requirements Errors
Why Do We Care?
Defining Organizational Goals and Objectives
Identifying Your Key Data
Data Management and Measurement
Quality Measures for Data
Baselines and Improvement Targets
Data Governance & Management Toolset
Data Improvement Plans
The Role of IT in Data Governance & Management
Issue Logging

Dealing with Connectivity
Issues With a Connected World
Addressing Issues with the Connected World
Examples of Issues with the Connected World
The Data Accountability Map
Data Accountability
Data Collection Governance Issues
Collecting Data
The Quality of Data Collected
Storing Data
The Governance Of Decision Making
Bias in the Decision-Making Process
Automated Decision-Making
Reporting on Data
Strategy for Reporting on Data
Data Classification for Reports
Distribution of Data
Aspects of Data Security
Models For Data Distribution:
Example: ENISA* Traffic Light Protocol
Why Dispose of Data?
Candidates For Data Disposal
Policy For Data Disposal
Creating Reports to Identify Disposable Data
External Triggers For Data Disposal
Permanent Removal
Archiving Data
Balancing Value, Risk, and Constraint
My Summary

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Data Governance and Maturity Training FAQs

40% of the course time is spent in hands-on exercises

Yes, this course is a perfect starting point for someone entering Data Governance

No, this course is technology neutral

This course applies to anyone looking for an introduction to data governance and including data maturity. Attendees will come from all types of industries, all with a common interest in data.

Job roles include: 

  • Senior Managers
  • Business Analysts
  • Data Analysts
  • Data Scientists
  • Database Administrators
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