Case Study: Dominion Energy Run-Time Efficiency Improved by 98% with Predictive Analytics

Using Big Data and the Cloud to Help Dominion Energy Gain the Power to Predict Demand and Reduce Their Ecological Impact

struggle harnessing image

A Challenge Harnessing Data

Dominion Energy needed to understand sales anomalies and accurately forecast customer demand to complete critical financial performance reports and manage energy usage.  

A workflow bottleneck prevented the company from performing effective data analysis on their customer population. With a large customer base, this resulted in slow, piecemeal data analysis. Lengthy processing times restricted analysts’ ability to deliver actionable marketing insights to company decision-makers. 

Dominion Energy sought a solution that could: 

  • Process large volumes of data
  • Integrate internal and external data
  • Allow their team to become more predictive and proactive. 

Additionally, they needed a data governance program to address data quality and integrity issues.

captech partners image

CapTech = Big Data Solutions

Dominion Energy asked CapTech to propose a modern data architecture solution and develop a roadmap that would allow them to set up, maintain, and utilize a big data insight platform.

Our Data & Analytics team:

  • Delivered a big data cloud solution that utilized open-source tools saving costs and easily integrating with existing systems
  • Created a platform that allowed data analysts to interact with large volumes of data from different sources and generate analytical insights
  • Quickly got the cloud tool up and running and able to process up to 40 terabytes of data
  • Developed a data governance policy that allowed the client to expand data practices across their enterprise and enable smart decisions
  • Implemented a data science community of practice and provided user training across departments 
power of data image

Tapping into the Power of Data

The cloud solution we executed has allowed the energy company’s analysts to access data in a fraction of the time that was previously possible. Query run-times have been reduced from a day to minutes, improving run-time efficiency 98% in some cases. This has freed up previously paralyzed analysts to respond to requests quickly and leverage data more effectively. Now that the client can store and analyze all of their data they can make better predictions of their customers’ energy usage. 

Leveraging data in new and powerful ways has empowered the energy company to better serve their customer needs and manage their products, as well as improve reporting to stakeholders. Impacts include:

  • Real-time monitoring of customer energy usage and outages
  •  Ability to proactively respond to power outages
  • 360-view of the customer for alignment with product offerings
  • More accurately prepare their supply to prevent blackouts and brownouts
  • Lower margins on excess energy production which saves money for both customers and the client
  • Utilize fewer resources and reduce their ecological impact

 The company is currently using this project as a blue print for ALL enterprise big data project.