Fizz.hu Turbocharges E-commerce Analytics

Hungarian e-commerce giant Fizz.hu has accelerated its analytics capabilities by migrating from Microsoft SQL Server to Databricks SQL. The three-month overhaul delivered faster reporting, a future-proof AI architecture, and empowered self-service analytics for its rapidly growing business.

StartupHub data

Companies working on this

Profiles of the companies named in this story, with funding and a one-liner from our database.

Databricks

$190.0B

A unified data analytics and AI platform built on the lakehouse architecture.

Palantir Technologies Inc.

$20.9

Data integration and analytics software company for government and commercial clients.

Google

$9.1B

Global technology leader in search, advertising, cloud, AI, and consumer electronics.

Power BI

A suite of business analytics tools by Microsoft for data analysis and interactive visualizations.

Launched two years ago, Fizz.hu hosts over 1.5 million product offers. Initially reliant on SQL Server and Power BI for daily batch reporting, the platform's limitations became apparent as its catalog expanded. Fizz required a unified solution capable of handling SQL, Python, and upcoming AI initiatives without adding operational complexity.

The company opted for a lakehouse architecture, a move that streamlines data management and unlocks advanced analytics. This approach aligns with modern data strategies, offering significant benefits over traditional data warehousing, akin to advancements seen in efforts to Build and Design a Data Lakehouse on Google Cloud Platform and similar unified data platforms like those explored by Palantir and Databricks.

Tamás Bácskai, Head of Data at Fizz.hu, spearheaded the migration with an MVP-first strategy. The team successfully migrated core data and views, repointing existing Power BI reports to the new Databricks engine.

This pragmatic approach resulted in a dramatic performance boost. Nightly ETL processes, once spanning three to four hours, now complete in approximately 90 minutes. Reporting is reliably available by 4:30 a.m., a significant improvement for early-starting business users.

Power BI refreshes are now 50% faster, and large data exports take mere minutes. These gains stem from Databricks SQL's efficient engine and auto-optimization, not just increased infrastructure spend.

Crucially, Databricks eliminated the need for separate Python environments, consolidating all workloads into a single, unified platform. This simplifies operations and lays a robust foundation for future machine learning and generative AI projects.

Looking ahead, Fizz.hu is leveraging Databricks for enhanced governance and AI-driven features. AI-powered SQL functions will automate data cleaning for product names, while Databricks Genie enables natural-language querying in Hungarian, democratizing access to data insights. This mirrors successful self-service analytics implementation seen in other large organizations.

Databricks SQL provides Fizz.hu with a scalable, AI-ready foundation to support evolving business needs, from marketing analytics to model deployment, without a corresponding increase in team size.