Case study
Major U.S. utility company improved advanced metering infrastructure data processing times by 300% with UST IQ on AWS Cloud
OUR CLIENT
Ranked as one of the largest energy companies in the world, this client serves approximately 40 million electric and gas utility customers in North America. The company generates nearly $15 billion in annual revenue and employs more than 15,000 people.
THE CHALLENGE
Utility company wanted to replace end-of-life AMI application with modern cloud solution
The utility company’s advanced metering infrastructure (AMI) solution was nearing its end-of-life. This situation was the optimal time to shift to a cloud-based SaaS subscription solution to minimize capital expenditures and deploy a more modern, agile infrastructure. Because of the company’s vast operations, it needed a robust solution that could process at least 24 TB of data annually from more than six million meters and approximately 4,500 data tracking units. The solution also needed to:
- Provide near real-time data processing capabilities.
- Generate 30-day rolling usage averages.
- Offer transparency so operations personnel could proactively identify issues.
THE TRANSFORMATION
Robust, flexible UST IQ on AWS Cloud met company’s rigorous data processing needs
After deploying UST IQ on AWS Cloud, the gas company had the modern SaaS solution it wanted. The project team created a cloud-based data warehouse to store and manage the enormous amount of data generated by the utility meters and data tracking units. UST IQ’s flexible data processing, curation, and analysis capabilities allowed the operations team to create dimensional models to generate the 30-day rolling averages, gain insights from the usage data, and identify potential problems as quickly as possible.
THE IMPACT
Utility company reduced AMI data processing timeframes by 300%
The new cloud-based AMI solution provided the robust data processing capabilities the company needed. Now, the operations team could analyze more than 300 million account records in less than two hours on a daily basis - a 300% improvement in processing time that far exceeded established performance SLAs compared to the legacy solution. With 5-minute micro-batch streaming, the company also gained the near real-time data processing it wanted. By migrating from a capital-intensive on-premises solution to a more cost-effective SaaS subscription solution, the company eliminated up-front CAPEX costs and significantly reduced its total cost of ownership.