Data Democratization Platform for IoT Analytics

Data Democratization Platform for IoT Analytics Using Databricks on AWS

A case study on how we enabled data access, visibility, and data-driven decision-making across IoT and product teams.

Client Background

Electrolux is a global leader in home appliances, with a strong focus on connected devices and IoT-enabled products. Their appliances generate large volumes of data through mobile apps and connected systems, providing valuable insights into how users interact with their products.

The organization includes multiple teams such as product, engineering, and data, all of which rely on accurate data to improve user experience and drive innovation.

Their customers include:

Consumers using connected home appliances
Mobile app users interacting with smart devices
Product teams building new features
IoT teams managing connected ecosystems

To support these teams, Electrolux needed a system that could make data accessible, reliable, and easy to use across the organization.

The Problem: Data Was Available but Not Accessible

Before this project, Electrolux had a large amount of data, but there was no clear way for teams to access or use it effectively.

Several challenges existed:

No visibility into how end users were interacting with appliances
Limited access to data for non-technical teams
Multiple dashboards across teams with inconsistent results
No unified view of data across systems
No historical data tracking for AI and analytics use cases
No clear way to track cloud costs per appliance

In addition, data was spread across multiple platforms, leading to duplication and high licensing costs, estimated at over $30,000.

Decision-making was often based on traditional research instead of real data insights, which affected product performance and revenue growth.

Electrolux needed:

A centralized data platform
Easy access to data for all teams
Consistent and reliable reporting
A scalable architecture aligned with data mesh principles
A foundation for future AI and analytics use cases

Solution Overview

Haseeb developed a complete data platform using Databricks on AWS to enable data democratization across the organization.

The solution focused on making data accessible to both technical and non-technical users while ensuring consistency and scalability.

The platform integrated data from IoT appliances, mobile applications, and other systems into a unified environment. It supported both real-time and batch processing, allowing teams to analyze data efficiently.

The core technology stack used in the project included:

Databricks for data processing, analytics, and dashboards
AWS for cloud infrastructure
Data pipelines for ingestion and transformation
Integration with IoT and mobile app data sources

This approach allowed Electrolux to move from disconnected systems to a unified data platform.

Data Analysts

Our in-house data analysts have a hands-on approach to data.

Companies analyzed

Last year, we were able to help nearly 50 companies.

Process

Data designers

Our designers have an extensive background in data analysis.

Visualizations made

From presentations to marketing materials and beyond.

Ongoing projects

Data changes, but our team stands by your side when you need us.

Results

Electrolux achieved:

A centralized data platform for all teams
Improved visibility into user behavior and appliance usage
Consistent reporting across departments
Reduced duplication and lower licensing costs
Better tracking of cloud costs and resource usage
A strong data foundation for AI and advanced analytics

The organization moved from limited access and fragmented systems to a unified platform that supports data-driven decisions.

⭐⭐⭐⭐⭐

“Working with Haseeb helped us bring structure and clarity to our data. The platform they built allowed us to access and understand our data in ways that were not possible before. We now have better visibility, improved decision-making, and a strong foundation for future innovation.”

IoT Data Team, Electrolux

We’ve Helped Them

We’ve partnered with many household brand names to deliver insights and solutions to their problems with big data.

Happy Clients

Don’t just take our word for it – our clients frequently stay in touch with us and work with us on future projects that require big data insights.

I work in agricultural consulting, meaning that we often need to use big and complex datasets to justify expensive investments for our clients. DataAI consultants helped us see the big picture with their visualization tools and expertise.

As the in-house supplier manager, it's sometimes had to understand which manufacturers work best for our needs. DataAI's data analysis helped us identify where we could save and which manufacturers worked the best for us in the long term.

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