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Momentum Energy Cuts Costs in Half and Processing Time by 30 Percent with Matillion ETL and Snowflake

One of our favorite things about the Data to Insights virtual summit that Matillion hosted in May was the opportunity to hear about some of the great results that Matillion customers have been able to achieve with our consulting partner Interworks. Here’s how one of those customers, Momentum Energy, saved both time and money by modernizing to a new cloud data architecture featuring Snowflake, Matillion ETL for Snowflake, and Power BI.  

Momentum Energy cuts costs and reduces processing time with Matillion ETL and Snowflake

Momentum Energy: Renewable energy Down Under

Momentum Energy is a division of Hydro Tasmania, one Australia’s leading clean energy business and its largest generator of renewable energy. Momentum Energy sells electricity generated from renewable energy to more than 300,000 customers across the continent. 

Moving from on-premises data and analytics to a modern cloud data architecture

For years, Momentum Energy had its data architecture in an on-premises enterprise data warehouse, a traditional architecture built on Microsoft SQL Server. However, the company experienced challenges getting data into the system from Salesforce and getting reporting on that data done in a timely manner to serve customers better. The SQL Server database and integration and transformation solution, designed initially in SSIS, required a sizable data team to maintain. Reporting was often a time-consuming activity, especially on something as high volume as interval meter data from the field. Designing and maintaining ETL workloads and integrations required a lot of coding. 

By modernizing to a cloud data architecture, Momentum Data was hoping to do several things:

  • Build a cloud-based reporting and business intelligence platform that could give timely insight on different aspects and factors of Salesforce data
  • Create an fast, flexible ETL system that required very little time and intervention from developers
  • Shorten the time it took to get data from source systems into the cloud data warehouse, and then into the business intelligence platform

Matillion ETL, Snowflake, and Microsoft Power BI: An end-to-end data stack in the cloud

For its new cloud data stack, Momentum Energy decided to modernize to a Snowflake cloud data warehouse, using Matillion ETL to get data into the cloud and transform it using the power of Snowflake. Microsoft Power BI rounded out the stack as the company’s cloud business intelligence platform. 

In order to justify the benefits of the new architecture, Momentum Energy’s data team ran a proof of concept using its largest data set, interval meter data, which required a lot of capacity and data crunching. The savings in time and resources to do analysis on interval meter data was significant. What’s more, using Salesforce data, it took just six weeks for Momentum Energy to have an end-to-end solution running with Matillion ETL, Snowflake, and Power BI, where the company had data flowing through and was capturing analytics. 

Easy to learn, easy to use

From the start, Matillion ETL for Snowflake was easy to learn and easy to use, enabling the data team to create workflows for data loading and transformation with out-of-the-box connectors and components. Designing the new framework went smoothly, and the costs of running the new data stack were half of what it took to run the same jobs in their legacy on-premises solution.  Momentum Energy was able to stage more than 1700 tables into Snowflake. 

“We didn’t have to go through lines and lines of code just to get this new data into Snowflake, which has always been a challenge in the past,” Bhavika Unnadkat, Head of Data at Momentum Energy. 

With the new system, the data team was also able to connect Power BI directly to Snowflake and refresh data nightly using Matillion ETL, significantly improving data freshness and time to insight. While with the legacy ETL system it took nine to 10 hours to load data, with Matillion ETL and Snowflake it takes just 2.5 hours to load data and delta changes. Finally, where it used to take a large data team to maintain Momentum Energy’s on-premises ETL and data warehouse solution, it takes just two people to maintain the new cloud data stack. 


  • Out-of-the-box connectors and components reduce time and complexity of jobs
  • Requires only two people to maintain
  • Data refreshes nightly
  • Cut licensing costs in half
  • Cut data loading and transformation time by 30 percent

More transformation, more data sources on the horizon

Now that Momentum Energy has the new cloud data stack and data lake implemented, the company plans to focus on increasing the amount of data transformations it is doing, and incorporating more data sources, more models, and other data scenarios to become even more insights-driven.  

Learn more about Matillion ETL

To learn more about how Matillion ETL can speed up data transformation and time to insight for your organization, request a demo