---
title: "Fizz accelerates ecommerce analytics with Databricks SQL"
description: "Fizz.hu, an ecommerce marketplace backed by OTP Group, outgrew a Microsoft SQL Server and Power BI setup that relied on daily batch loads and separate virtual-machine Python workloads. The company migrated about 50 tables and several stored procedures to Databricks SQL, recreated core views, and moved to a lakehouse architecture using an MVP-first approach rather than redesigning everything. Completed in three months, the migration switched off SQL Server while keeping Power BI reports running on the new engine. Nightly processing fell from three to four hours to roughly 90 minutes, reports became consistently available by 4:30 a.m., Power BI refreshes dropped about 50%, and gigabyte-scale exports finish in minutes. Databricks now unifies SQL, Python, machine learning, governance work, and Hungarian-language Genie self-service, with about 20 users reclaiming roughly 20% of an analyst’s time."
---

# Fizz accelerates ecommerce analytics with Databricks SQL

[Databricks](https://yomu.fyi/company/databricks) · Tamás Bácskai, Istvan Viz · Sep 18, 2026

**Type:** Problem & solution

## Summary

Fizz.hu, an ecommerce marketplace backed by OTP Group, outgrew a Microsoft SQL Server and Power BI setup that relied on daily batch loads and separate virtual-machine Python workloads. The company migrated about 50 tables and several stored procedures to Databricks SQL, recreated core views, and moved to a lakehouse architecture using an MVP-first approach rather than redesigning everything. Completed in three months, the migration switched off SQL Server while keeping Power BI reports running on the new engine. Nightly processing fell from three to four hours to roughly 90 minutes, reports became consistently available by 4:30 a.m., Power BI refreshes dropped about 50%, and gigabyte-scale exports finish in minutes. Databricks now unifies SQL, Python, machine learning, governance work, and Hungarian-language Genie self-service, with about 20 users reclaiming roughly 20% of an analyst’s time.

## Context

Fizz.hu began with Microsoft SQL Server and Power BI for reporting, using daily batch loads. As its marketplace grew beyond 500 merchants and 1.5 million active product offers, the setup’s separate Python environment, limited governance, and infrastructure scaling requirements became constraints.

## Approach / What changed

Fizz adopted a lakehouse architecture centered on Databricks SQL and used an MVP-first migration. With external support, the team moved approximately 50 tables and several stored procedures, recreated core views, redirected Power BI reports to Databricks, and refined the platform after the legacy SQL Server was retired.

## Takeaways

- Fizz completed its migration in three months by moving core tables, procedures, and views first instead of attempting a full redesign before switching platforms.
- End-to-end nightly processing decreased from three to four hours to roughly 90 minutes, while Power BI refresh cycles fell by about 50%.
- Databricks Genie lets about 20 users ask questions in Hungarian without SQL, reclaiming roughly 20% of an analyst’s time spent on ad hoc requests.

## FAQ

### Why did Fizz use an MVP-first migration instead of redesigning everything?

The team wanted to move quickly while keeping reports running, then refine and modernize after the data was in Databricks. It migrated core tables, stored procedures, and views rather than pursuing a perfect rewrite.

### What performance improvements did Databricks SQL deliver?

Fizz reduced its nightly processing window from three to four hours to roughly 90 minutes, with reports consistently ready by 4:30 a.m. Power BI refreshes fell by about 50%, and gigabyte-scale exports complete in minutes.

### How does Databricks Genie affect analysts and business users?

Business users can ask natural-language questions in Hungarian without writing SQL. About 20 active users currently rely on Genie, reclaiming roughly 20% of an analyst’s time previously spent answering ad hoc requests.

**Tags:** [AI](https://yomu.fyi/topic/ai), [Architecture](https://yomu.fyi/topic/architecture), [Databricks](https://yomu.fyi/topic/databricks)

- Source: [Databricks](https://www.databricks.com/blog/fizz-accelerates-ecommerce-analytics-databricks-sql)
- Source URL: https://www.databricks.com/blog/fizz-accelerates-ecommerce-analytics-databricks-sql
- Ingested by Yomu: 2026-09-17T14:12:54.892Z

[Read original post](https://www.databricks.com/blog/fizz-accelerates-ecommerce-analytics-databricks-sql)