EMPRIS
Tool to explore energy market data
Overview
Context
ElectraLink runs core infrastructure for the UK energy market, providing data that analysis teams rely on every day. EMPRIS was built to help people make sense of large, complex datasets. The platform brings structure and clarity to work that was often manual, making it easier to explore and understand the information at hand.
Challenge
Working with energy data is detailed and time-consuming, and teams need to trust what they see. People need to explore the information, check it, and draw conclusions without missing important details. The challenge was to make the data easier to navigate and understand while keeping the full picture visible, giving everyone confidence without simplifying too much.
Research
We worked directly with the Energy Market Analytics team, observing how they utilised existing tools and talked to them about their routines and decisions. It became clear that seeing context early, having clear notes about datasets, and keeping the underlying data accessible made interpretation easier. Showing both summaries and the original data helped people feel confident in their work. These observations guided how we organised the interface and structured the way information is presented.
Logging in
Orienting users from the start
When users log in, they arrive on a personalised dashboard highlighting recent activity, priority alerts, and relevant datasets. We structured the widgets to guide attention to what mattered most while keeping the interface approachable for all skill levels. This design reduces time spent locating relevant datasets or ongoing analyses and helps users begin work with confidence. Early feedback showed users were able to start tasks more efficiently and spent less time figuring out what required immediate attention.
Browsing datasets
Selecting relevant datasets confidently
Users explore datasets through a marketplace-style interface where each card displays ownership, refresh cadence, geographic scope, and a brief description. Filters allow them to narrow results by relevant criteria. We prioritised surfacing this context upfront so that users could select datasets with confidence and reduce the need for cross-checking. Analysts and business users reported faster dataset discovery and fewer errors, which allowed them to prepare queries and analyses more efficiently.
Building and running queries
Exploring data and sharing insights
In the query editor, users write SQL while the interface keeps the data context visible. Once a query runs, results appear in parallel panels showing charts, raw records, and export options. This layout reduces back-and-forth verification, helps teams confirm assumptions, compare outcomes, and share findings confidently, making analysis faster, more transparent, and easier to act on.
Impact and reflections
Strengthening transparency and trust
The MVP helped partner teams move from spreadsheets to exploring billions of renewable-generation datapoints efficiently, keeping raw data visible alongside visualisations to build confidence in results. We learned that transparency (making recommendations and derived insights clear) is key to trust. Looking ahead, guided onboarding, contextual insights, and collaboration features can support diverse users, while accessibility improvements ensure the platform works for everyone.