Class Hours: 8:00am-5:00PM
Fees:

UAI Member: $695 before 3/8, $795 after 3/8
Non Member: $995 before 3/8, $1095 after 3/8

The Utility Industry is evolving and adapting to new regulations, changes in public perception and emerging market opportunities. Drivers of change include aging infrastructure, opportunities for decarbonization, the need for sustainability, cyber-security and moving towards green energy. Enabling modern data resources and capabilities to assist with these challenges is critical for success.

The world of data management also continues to change, but data governance doesn’t always keep pace. New governance practices and organizations are needed to be compatible with agile, big data, cloud, and self-service to support the changing business dynamics. 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 needs to ensure that internal data literacy and strategies continue to be aligned with the evolving business goals. It also needs 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.

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.

What you will learn:

• Where governance fits within modern data ecosystems in the utility industry
• Process challenges for supplementing controls with collaboration and crowdsourcing
• Organizational challenges for moving from data stewards to stewardship, curation, and coaching
• Operational challenges for implementing a combination of gates, guardrails, and guides
• Why data ethics is a data governance challenge and how to begin tackling the issue
• Why you need to transition from traditional data stewards to stewardship, curation and coaching
• How to use a data governance framework plan for data governance modernization and evolution