NextEnergy: Data-driven growth built on a solid foundation

NextEnergy is a fast-growing scale-up in energy technology. The company offers dynamic energy pricing — rates that can vary by day or even by hour. By using energy at the right moments, customers can significantly reduce their energy bills. With this innovative market model, the organization has grown rapidly in a short period of time.

NextEnergy is a fully digital organization. Quatronic laid the foundation for this digital setup by developing the complete customer registration portal, back office, and mobile customer app. All of this was built using OutSystems’ low-code platform — in just six months. After delivery, the software was transferred to NextEnergy so their team could continue developing and expanding the applications themselves. The organization also uses Microsoft solutions such as Dynamics and Azure.

The challenge: from big data to reliable insights

NextEnergy works with enormous amounts of data — from smart energy meter readings and billing information to registration and marketing data. The smart meters alone generate new data every hour for each individual connection.

When questions arose that needed to be supported by data, quick ad-hoc queries were often created to pull information directly from the source systems. This led to datasets with different definitions and metadata, a large number of ad-hoc reports, and no way to consult historical data.

To combine data from different systems, Excel was often the go-to tool — pragmatic, but with major limitations, especially when working with large datasets. The result was a slow and ad-hoc process. And as the company continued to grow, data reliability became increasingly important for making sound strategic decisions.

Building the solution together

CFO Gert-Jan Kampkuiper — who brought experience in finance and business intelligence from PwC and Signature Foods — immediately saw the need for a solid foundation to enable reliable reporting.

Before any dashboards were built, the management team and Quatronic defined the most important KPIs. Some of these were highly data-driven. Quatronic translated these KPIs into the existing source systems, ensuring uniform data, proper use of timestamps, and a centralized storage location.

The first step? Setting up a data lake to bring together all relevant data from the different source systems.

The solution: a scalable data lake in Azure Synapse

Quatronic implemented the data lake in Azure Synapse — an all-in-one platform for data loading, storage, and analysis. By separating the analytical environment from the operational one, the organization ensures stable performance even during complex analyses.

The platform was also designed to support self-service analytics, enabling employees to create their own reports without being dependent on a data analyst.

The data lake was built using the medallion architecture, consisting of three layers:

• Bronze: raw, unprocessed data from the source systems.
• Silver: structured data enriched with historical perspective — ideal for analyzing trends such as customer onboarding times or invoice payment terms.
• Gold: combined, cleaned data that’s ready for reporting and analysis.

Excel reports that previously had to be updated manually are now directly connected to the gold layer and automatically refreshed with the latest data.

“In our weekly management update, I can now access the most up-to-date information at the touch of a button. That alone saves so much time.” – Gert-Jan Kampkuiper, CFO NextEnergy

A stable data lake also provides flexibility: new data sources can be added quickly, ensuring that all reports draw from one central source — so everyone is working with the same reliable information.

The future

The next step is to further expand data analysis and visualization. Soon, a digital dashboard will replace the physical whiteboard in the finance department — making real-time insight the new standard.

“We can now support our gut feeling with data.”

In the coming period, NextEnergy will focus on training employees and embedding this new data-driven way of working. The ultimate goal: gaining deeper insights and making reliable predictions based on data.

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