UAI TRAINING COURSES
UAI’s missions is to enable utility transformation through analytics and we will continue to deliver on our mission with the addition of UAI Training. We launched training to help professionals improve skills on a range of industry topics centered around data and analytics.
Utility Analytics 101
Utility Analytics 101 is creating better citizen data scientists. This training is an introduction to utility analytics. You will learn about utility analytics terms and relationships, and about the world of data, including big data, databases, data structures, and data types. You will benefit from learning about utility analytics uses cases in various focus areas like asset health analytics, customer analytics, grid analytics, and safety analytics. You will explore data analysis and data prep with SQL. There is an introduction to and demonstrations of the fundamental concepts and best practices of data visualizations and you will learn how best to communicate results from your data analysis. Lastly, you will get time for application work and you will put it all together with Python.
Utility Analytics 201: Applied Machine Learning for Utility Professionals
This training introduces ML, including the concepts of exploratory data analysis, supervised learning (classification and regression), and unsupervised learning (dimensionality reduction and clustering). Participants will apply concepts through guided, hands-on activities.
Modernizing Data Governance for Utility Companies
The world of data management 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. Building beyond enforcement to prevention, controls to services and committees to communities are at the core of data governance evolution.
Data Quality in Utilities: Concepts and Best Practices
Data quality is a large and complex field with many dimensions. Every data quality practitioner needs a foundation of concepts, principles, and terminology that are common in quality management. Building upon that foundation, they need to understand how quality management concepts and principles are applied to data, as well as the language and terminology that specifically apply to data quality. The importance of data quality in the Utility industry is rapidly growing as new use cases for analytics are identified and pursued.
Finding Meaning in Utilities Data: Visualization and Storytelling
Analytics effectiveness and impact depends on visualization skills of two kinds – ability to create visuals and ability to understand visuals. The real value of visualization does not come from creating visuals, but from understanding what they tell you. With the language of words, we learn reading and writing as separate but related skills. Similarly, with visual language we need to learn understanding (reading) and creating (writing) as distinct but related skills. Data analysts at the top of their game go beyond creating data visualizations. They add narratives to interpret the visuals and to explain insights and recommendations. In short, they tell data stories.
Root Cause Analysis in Utilities: The Art and Science of Knowing Why
Understanding why things happen is a fundamental management skill. For anyone who is challenged to manage data quality, business processes, or people and organizations, finding root causes is an essential skill. Understanding why is the key to knowing what to do – the core of sound decision making. But cause-and-effect relationships are elusive. Real causes are often difficult to find so we settle for easy answers. This leads to fixing symptoms rather than to solving problems, and to little or no gain where opportunity is abundant. Root cause analysis is the alternative to easy answers. Looking beyond the apparent and obvious to find real causes brings insight and sows the seeds of foresight.
202: Introduction to Forecasting in the Utilities
Continued population growth, socioeconomic improvements, and technological advancements in the past few decades have caused a significant rise in the consumption of energy and materials. Many utilities find themselves concerned -- the volatility of wind and solar power generation, the uncertainty of rooftop solar adoption, and rising gas and electricity prices all pose serious challenges. The modern consumer centric paradigm of transactive energy has changed the traditional load forecasting methodologies, as it evolves and reshapes utility strategies. This training intends to provide a comprehensive introduction to forecasting methods and to present enough information about each method for participants to be able to use them sensibly. Examples and applications from the utility industry, including forecasting with AMI data, are included.
More information coming soon!