Utility Analytics 101 – February 25-27, 2025
The Utility Analytics 101 course is a three-day workshop for professionals in the utility industry and covers key topics in analytics, database fundamentals, data preparation, and visualization, with a focus on smart meter data. Participants will learn how analytics can optimize operations in utilities, including safety, predictive maintenance, and sustainability efforts. The workshop introduces machine learning applications in utilities, discusses the importance of data integrity and security, and explores big data infrastructure like Hadoop and Spark. Through hands-on exercises, participants will design and build databases, clean and prepare data, and visualize insights. Additional topics include time-series data handling, anomaly detection in smart meter data, and data quality metrics. By the end of the workshop, participants will have the skills to apply analytics to real-world utility scenarios, ensuring data-driven decision-making in their organizations.
Speakers
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Sridhar RadhakrishnanCo-Director, Data Science and Analytics Institute Interim Associate Dean for Partnerships, Gallogly College of EngineeringSridhar Radhakrishnan has been a faculty member at OU since the fall of 1990. He completed his Ph.D. in computer science from Louisiana State University and earned an MS in Systems Science and an M.L.I.S degree. He completed his B.Sc in Physics from Vivekananda College, University of Madras, India, and a B.S. in Computer Information Systems from the University of South Alabama, Mobile, Alabama. His research areas include graph algorithms, high performance computing, computer networks, and computational finance. He has published numerous research monographs and a textbook on Data Structures. He has been a PI and a co-PI on many research grants from state and federal agencies, and industry. He is a member of the ACM and a senior member of the IEEE. He currently serves as one of the commissioners for the computing accreditation commission of ABET.
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Ashesh GaurGraduate Teaching Assistant (PhD Candidate), The University of Oklahoma
Pricing
Virtual Training
In-Person Training
Virtual Training
UAI Member
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Regular Pricing: $695
Non-Member
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Regular Pricing: $895
In-Person Training
UAI Member
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Regular Pricing: $1595
Non-Member
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Regular Pricing: $2095