Module 0. About the Course (6 min)
Module 1. Big Shifts in Data Management (32 min)
The world of data management has changed substantially in recent years, but data governance hasn't kept pace. New governance practices and organizations are needed to be compatible with agile, big data, cloud, and self-service. Moving from control to community, from enforcement to prevention, from controls to services, and from committees to communities are at the core of data governance evolution.
Traditional data governance practices need to adapt to the realities of today’s data management practices. We need to start with the ABCs of modern governance — Agile, Big Data, and Cloud. Each of these has been in the mainstream for several years, yet most data governance organizations cling to practices of the past. More recently, self-service analytics and self-service data preparation have challenged the old governance methods.
You will learn:
Traditional data governance focuses on enforcement of policies and rules using rigorous controls and gates. While controls and enforcement continue to be needed, they must be complemented with support for the autonomy and agility of the self-service world. Enforcement works together with prevention. Guides and guardrails reduce the need for gates. The need to exercise controls is minimized when curating, coaching, crowdsourcing, and collaboration are integral parts of governance processes. In the modern data world, every data stakeholder plays a part in data governance.
This course is geared towards:
- Where governance fits within modern data ecosystems, from point of ingestion to reporting and analysis
- How various technologies support governance through the ecosystem
- Process challenges for governing self-service; supplementing controls with collaboration and crowdsourcing
- Engagement models for governing self-service
- Organizational challenges for governing self-service; moving from data stewards to stewardship, curation, and coaching
- Operational challenges for governing self-service; implementing a combination of gates, guardrails, and guides
- Data governance professionals of all types
- Data stewards and data curators
- Business and technical leaders implementing and managing self-service data and analytics
- Business and technical leaders who see current data governance practices as barriers to agility
- Chief Data Officers and other executives responsible to shape data culture
- Everyone with a role in modernizing data governance or an interest to know how and why data governance must change
Module 2. Data Governance Through the Information Supply Chain (29 min)
- The World of Legacy BI: Data Integration the Old Way
- Technology Revolution
- Modern Data Ecosystems
- The World of Modern Analytics
- The Magnitude of Change: How Big the Change Really Is?
Module 3. Technologies and Modern Data Governance (13 min)
- Protection, Utility, and Value
- Raising New Questions
- Data Protection
- Data Utility
- Data Value
Module 4. People, Processes, and Modern Data Governance (35 min)
- Technology Across the Ecosystem
- Bringing Data into the Ecosystem
- Curation, Cataloging, and Metadata
- For Analysis-Ready Data
- Data Usage
- Across the Ecosystem
Module 5. New Challenges in Data Ethics (44 min)
- Changing Governance Practices: The Challenges
- The Tensions
- Rethinking Policy Enforcement
- Rethinking Complexity
- Rethinking Process Rights
- Rethinking Process Rigor
Module 6. Next Steps to Modern Data Governance (24 min)
- The Trouble with Ethics: Ambiguity and Uncertainty
- Ethics Defined: What Does It Mean?
- Governance and Ethics
- Data and Ethics
- Managing Data Ethics
- A Modern Data Governance Framework: The Big Picture
- Modernization Roadmap
-here- to download a more detailed outline of this course.
This exam tests knowledge and understanding of concepts, principles, and terminology of data stewardship.
You will be tested in these areas:
- The forces that drive need for data governance modernization
- A modern information supply chain and where data governance fits in
- The data governance features and functions of data management and analytics technologies
- The human side of data governance and the changes that are needed
- The process dimension of data governance and the changes that are needed
- The concept of data governance as a service
- The emerging challenge of data ethics
Number of Questions: 23
Time Limit: 46 Minutes
Passing Score: 70%
Once you pass the exam, you will receive a Certificate of Education documenting that you have demonstrated mastery of the topic. Further, the exam counts towards
Certified Information Management Professional (CIMP) designation in the Data Governance track.
We recommend that you take detailed notes and review the course material multiple times before taking this exam.
Click here to learn more about CIMP exams.