With greater focus on new forms of energy and technological progress in the space of solar energy, the world in which traditional power utilities operate has been going through significant change. Integral Analytics helps power utilities be on top of this change by helping them tap into other sources of data, such as econometrics and customer-owned power assets, to learn how customers currently use power and how that usage will likely change over time. This helps the power utilities plan the right level of resources and be well positioned for the future. For example, by fusing econometric data with traditional load data, utilities can gain valuable insights on the future growth of electrical load for better planning.

A key piece of the solution that Integral Analytics delivers involves extracting intelligent insights from huge amounts of data – workloads can run up to 25 TB of data, including text data and aggregates from meters, transformers and substations.

Integral Analytics (IA) deployed the first version of their solution on Amazon Redshift, but ran into limitations related to the offering and costs. For IA, not being able to pause the instance when not in use proved to be a hassle. IA had to take a snapshot of the data for backup purposes and then get rid of the entire instance. Looking to reduce costs, the IA team found the complete offering from Azure much more compelling. Some of the key reasons IA chose Azure SQL Data Warehouse were the ease of scaling an instance, instance pausing for cost optimization, support for .NET tools, flexibility of scaling compute, and storage separately. IA was also impressed with the easy integration of advanced analytics tools like Azure Machine Learning.

Learn more about Integral Analytics switch to Azure from AWS.

In the words of Bill Sabo, Managing Director of Information Technology, Integral Analytics, “When we learned about the pause and resume capabilities of SQL Data Warehouse and integrated services like Azure Machine Learning and Data Factory, we switched from Amazon Redshift, migrating over 7 TB of uncompressed data over a week for the simple reasons of saving money and enabling a more straightforward implementation for advanced analytics. To meet our business-intelligence requirements, we load data once or twice a month and then build reports for our customers. Not having the data-warehouse service running all the time is key for our business and our bottom line.”

IA chose Azure SQL Data Warehouse not only for the differentiated capabilities it delivers, but also because of its integration with various products within Azure to provide a full end to end solution – from data storage and processing to advanced analytics and intelligent insights.

Quoting Kevin Kushman, COO, Integral Analytics – “Azure SQL Data Warehouse is a fundamental part of our IT ecosystem. Cloud-based data solutions like Azure are going to be crucial for data-intensive companies like ours.”

Learn more about the story of how Integral Analytics is using Azure SQL Data Warehouse.

If you have not already explored this fully managed, petabyte scale cloud data warehouse service, learn more at the links below.

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What is Azure SQL Data Warehouse?
SQL Data Warehouse best practices
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