01.01.2023 / 08:24
Podcast: Data Science Mini-Series
Data Science
The data science miniseries is a deep dive into how the energy industry uses data science to make better decisions, reduce operational costs, and implement efficient scalable distributed energy. Unfortunately, hype and unrealistic expectations often lead to misunderstandings and confusion about where and how to take advantage of current and emerging data science tools.
Topics range from data science fundamentals, trading, operations, forecasting, distributed energy, working with large data sets, and even skills required.
We understand data science impacts all aspects of the energy business. Hosts Chris Sass and Selina Reinicke use a series of interviews with industry leaders and subject matter experts to build and share an understanding of where data science fits today and into the future of energy.
Episode 1 - Eric Sobolewski from TLGG
Data science is incredibly relevant for the energy industry, but unrealistic expectations and hype can lead to confusion and misunderstanding. In this episode our hosts Selina Reinicke and Chris Sass, together with their guest Eric Sobolewski from TLGG, lay the groundwork for this series. What are all the buzzwords about? How much data should your company keep? What's a data maturity model? What role do renewables play in the data science world? So many questions: ready for the answers?
Episode 2 - Martin Fengler from Meteomatics
In this episode, Martin Fengler, CEO at Meteomatics, joins our hosts, Chris Sass and Selina Reinicke, to shed light on the data science behind weather forecasting, the tools required, and its application in the energy industry. From weather drones flying as high as six kilometers to supercomputers used to handle vast datasets, this episode will guide you through it.
Episode 3 - Richard Büssow from Industrial Analytics
In this episode of our data science podcast, The Insider's Guide to Energy, our guest is Dr. Richard Büssow, the Co-Founder of Industrial Analytics. Dr. Richard Büssow joins our hosts, Chris Sass and Selina Reinicke, to shed light on predictive maintenance and the data science involved. Interested in what a "digital twin" might be and how data science and engineering combined by some clever minds are changing the energy industry? In this episode, it gets practical! Don't miss out!
Episode 4 - Edouard Alligand from Quasar AI
The fourth episode of our data science podcast together with Insider’s Guide to Energy has just been released. Our hosts Selina Reinecke and Chriss Sass explore time-series data and question efficient ways of storing and retrieving the nowadays vast amount of gathered data. The guest Eduoard Alligand, who is the CEO and founder of Quasar AI, helps them dive deep into the realm of scalable data based on their innovative software. It's widely recognized that accurate forecasting plays a pivotal role in modern trading. However, the true competitive edge lies in the immediate organization of collected time-series data in a structured and granulated manner. Curious and eager to learn more about real-life applications?
Episode 5 - Dr. Sven Orlowski from EWE Trading
During this insightful episode, we explored the remarkable transformation that has taken place within the industry and shed light on the vital role of change management in embracing data-driven energy trading. We also emphasized the significance of data literacy and skills, discussing how they contribute to success in this dynamic field. Don't miss out on this golden opportunity to expand your knowledge and stay ahead in the ever-evolving energy trading landscape. Tune in now to gain valuable insights!
During this enlightening episode, Hubert and Tom will explore a wide array of fascinating topics, including the various data types and volumes involved in energy trading, the intricate processes of data processing, as well as the exceptional adaptability and flexibility of Dexter Energy's solutions. Their expertise and insights are sure to provide valuable and eye-opening perspectives on the innovative applications of data science in the energy trading sector.