How Power BI makes the energy sector more efficient

About Webinar

Energy is central to most of the challenges and opportunities that you see in daily life. The energy sector is evolving, and with it the data generated by utilities companies increases as well. Although, this massive amount of data can be deployed to analyze and visualize insights across all the dimensions of various business processes. This, in turn, helps companies to take savvy operational as well as business decisions.

"Gartner analysts predict that by 2025, 80% of data analytics initiatives that are focused on business outcomes will be considered an essential business capability."

To leverage the benefits of data analytics, organizations can adopt tools like Power BI. Firms can reduce environmental impact by gaining real-time visibility of operations across the energy value chain. AI-powered data analysis and visualization gives businesses opportunities to explore the demands and supply of energy. This enables an increased share of renewable energy.

In this webinar, our experts will discuss the key challenges that energy providers face. They will also focus on major use cases of data analytics using Power BI.

Webinar agenda

• Challenges faced by energy solutions providers
• How data analytics can address business problems facing the energy sector
• Power BI helping companies offer energy efficient solutions
• Data analytics use cases for the energy industry
  • -  Leverage customer insights to predict demands
  • -  Offer renewable energy sources
  • -  Become people-centric
  • -  Provide sustainable solutions with AI-driven analysis

Questions & Answers

The following are the answers to the questions that were asked during the live webinar.

Question 1: Our data is very old. How do we incorporate those datasets in Power BI?

Answer 1: You can leverage historical data that is stored in data sources like Azure Blob Storage, Azure Data Lake, Cosmo DB, Excel, Google Sheets, etc. These data sources can be easily integrated with Power BI. This ability makes the tool stand out of the competition. So, definitely you can turn your historical data into a strategic asset to make informed decisions.

Question 2: You mentioned that Power BI has ML and AI capabilities, so can you build your own models or are there any in-built models to use?

Answer 2: There are several features of Power BI like Dataflow, Cognitive Services and Automated Machine Learning or AutoML that can help you in building your algorithms. You can create or train the model according to your requirements to get predictions or forecasts as per the data that you feed.

Question 3: Can they showcase some KPIs related to the expenses and interests?

Answer 3: Apart from the KPIs we mentioned in our demo for the oil and gas industry we can incorporate other metrics that are crucial for the oil and gas industry such as:

• Top level parent for the depletion & depreciation account
• Sublevel accounts that separate depletion items from depreciation items
• Cash flow
• Interest expense
• Lease operating expenses
• Revenue pricing
• CapEx information like forecast and volume time shif
• G and A accounts information and many more as per your requirements

Question 4: What are some of the KPIs for drilling operations?

Answer 4: There can be several KPIs for drilling operations, based on your requirements. However, there are a few that comes to my mind like:

• Departmental operating budgets
• Acreage distribution and well count trends
• Regulatory requirements on drilling and production operations
• Commencement of drilling operations
• Acquisition analysis