Managing Energy Data: Advanced Analytics PD772328

Topics: Advanced Technologies Energy storage systems , Batteries , Data management , Cybersecurity , Big data , Sustainable development , Electric power grid , Smart grid

Introduction to Managing Energy Data:

The Internet of Things (IoT) revolution (eg. the vast spread of smart meters worldwide) is generating massive amounts of energy data, drastically transforming the sector and current energy systems. This digital transformation gives rise to more intelligent ways of managing energy and brings about opportunities for energy companies to improve their business models and services. This course contains a brief introduction to the topics presented in the course, from smart meters and smart metering data to data science.

Exploratory data analysis and data pre-processing:

Any data science project needs to start with exploratory data analysis and data preprocessing. These are key steps to ensure the required quality of data in order to develop a valid model data science model. Preparing the data to develop a data science model can take up to 80% of the efforts of the whole data science process and managing these steps is key to guarantee the accomplishment of the defined goals.

Customer segmentation:

Like in any successful business, not knowing our customer is out of the question. With the upsurge of energy big data, data analytics gives a breakthrough in this domain. Looking at consumption profiles and including other types of data, there is a massive opportunity to develop the right models that will let us know our clients. Coupling the right set of marketing strategies, an unprecedented value can be delivered.

Energy forecasting:

One of the most explored data science applications in energy-related data is forecasting. There are various uses and advantages related to energy forecast, which stand as one of the keystones in reaching for greener and smarter grids, posing the future of our energy systems.

Data science as a way to create value:

This course describes more concretely how data science can bring value to energy businesses. We explain why churn rate is increasing in utilities and why selling kWh is no longer an interesting business. Data science can bring a new generation of high value services that can transform the energy industry and actually bring value to a whole value-chain with a focus on efficiency and renewable energy sources. This courses closes with a focus on the final customer and how customer satisfaction can be achieved with advanced analytics to tailor services to their needs.

Business models strongly based on data science:

So, how to translate concepts and knowledge into successful businesses from scratch? This course provides a real-life insight on successful stories behind companies strongly based on data science, explaining how they have been able to deliver high value to their clients and also sharing real insights on their journey.


  • Explain how data science can bring value to the energy sector
  • Evaluate the implications, challenges and benefits of implementing data science projects in an energy company
  • Apply lessons learned from real-life business cases in which data science was applied to energy big data
  • Supervise the development and implementation of a data science project and create new value with the available data
  • Evaluate the impact of electrification on the system-wide peak electricity demand and the role that smart charging, demand management techniques and energy storage can play in mitigating these effects

Is this On Demand Course for You?

Senior operations personnel in energy utilities (distribution system operators, energy suppliers) and industry. Energy entrepreneurs.

For More Details

Email, or call 1-877-606-7323 (U.S. and Canada) or 724-776-4970 (outside US and Canada).

Access Period: 365 Days      CEUs: 1.5

Duration: 15 Hours