Electrolux Group, a 100-year-old global appliance manufacturer, is transforming how it uses data from connected products to inform decisions and improve customer experiences. Operating on a Data Mesh principle with its Global Data and AI platform at the core, Electrolux saw appliance data scale across regions, systems and formats. At the same time, product teams struggled to access timely insights. With Genie and AI/BI Dashboards on the Databricks Platform, the team behind Electrolux' connected appliance data replaced fragmented reporting and Slack-based workflows with governed, self-service analytics. Teams can now explore appliance usage in natural language, accelerating decisions and advancing data democratization across the business.
When appliance insights depended on fragmented data and manual requests
Electrolux is evolving beyond hardware to deliver connected, software-driven appliances that improve over time. To support that shift, the company built its AI and data strategy around three priorities:
- Focusing on strategic business areas to maximize value delivery with AI.
- Empowering employees and teams through data and AI democratization.
- Building robust foundations that allow governed scaling and cost discipline.
That third pillar shaped how Electrolux organized its data. The appliance manufacturing giant operates on a Data Mesh principle, with its Global Data and AI platform (GDAI) at the center and domain-specific platforms aligned to that foundation.
But as connected appliances scaled, the data they generated grew harder to manage. Appliance data arrived in different formats across the IoT, often deeply nested and inconsistent across models. Preparing it required significant cleansing, parsing and transformation before it could be used.
“The data was there, but it was messy and scattered,” said Valeria Ragagnin, Engineering Manager at Electrolux Connectivity Domain. “A lot of our work was just making it usable.”
For product teams, this created friction. Insight requests were handled manually via Slack, where data teams ran queries and returned results. Even simple questions could take hours or days, and knowledge remained siloed.
“It often depended on who you asked,” said Tim Cederkäll, Product Manager, Data Platform, Electrolux Connectivity Domain. “The logic behind those queries wasn’t shared, and that slowed everything down.”
As demand for data grew, Electrolux needed a way to make trusted insights directly accessible to business users without increasing reliance on data teams.
Enabling self-service insights with Genie and AI/BI
Electrolux addressed these challenges by building its Trantor data platform on Databricks and introducing Genie and AI/BI Dashboards as the primary interface for business users.
The team structured data using a medallion architecture, creating a curated Gold layer with clear, denormalized tables designed for consumption. Unity Catalog adds governance, metadata and discoverability, giving Genie the context it needs to interpret natural-language queries accurately.
“Genie only works if your data is understandable,” said Hajar El Hanafi, AI and Data Transformation Lead at Electrolux. “It pushed us to invest in the semantic layer and improve data quality.”
AI/BI Dashboards provide a streamlined view of core metrics such as connected appliances, churn, provisioning success and feature adoption. Genie extends this experience by allowing users to ask follow-up questions directly from dashboards or in dedicated Genie spaces.
Instead of navigating filters or submitting requests, product teams can now ask questions like how appliance usage varies by country, which features drive engagement or how behavior changes after a release.
“The questions didn’t disappear,” Tim said. “They just stopped needing us to answer them.”
The platform also supports use cases beyond reporting. Electrolux built a remote diagnostics pipeline that prepares appliance-specific data for service technicians before they arrive, improving first-time fix rates and reducing environmental impact.
Scaling data democratization across the business
With Genie and AI/BI, the Electrolux Connectivity Domain has shifted from fragmented reporting to a scalable, self-service model.
Product teams can now explore appliance data independently, reducing reliance on manual analysis and freeing up data team capacity. Tasks that previously required dedicated analyst support can now be handled directly by business users. That same connectivity also creates direct value for end customers. Remote diagnostics, for example, allow Electrolux to identify and resolve appliance issues without dispatching a technician, cutting wait times, reducing unnecessary callouts and lowering the environmental footprint of every service interaction.
“Now people can just ask and get answers immediately,” Tim said. “That changes how quickly we can make decisions.”
At the same time, Electrolux consolidated its reporting footprint, migrating 100% of Appliances dashboards to Databricks AI/BI. This eliminated redundant reports, reduced maintenance overhead and removed costly processing tied to legacy tools.
“We simplified everything,” Valeria said. “Now it’s easier for users and easier for us to manage.”
Genie also provides visibility into how data is used. Teams can analyze queries to identify common questions, improve data definitions and prioritize new dashboards.
“Before, insights lived in notebooks or Slack messages,” Tim said. “Now we can see what people actually need and improve the data accordingly.”
Conversational AI is one of the main drivers of Electrolux' second strategic pillar: empowering employees through the democratization of data and AI. Finance and supply chain are both embarking on their own Genie journeys alongside the Connectivity domain, built on the same governed foundation in GDAI. As more domains come online, Electrolux is working toward making 50% of its governed data products in GDAI accessible through Genie by 2029.
“Genie is making data democratization real,” Hajar said. “Each domain moves at its own pace, but they all build on the same governed foundation. That is how a 100-year-old company scales AI with discipline.”