citizenM - From one connected data source to a full-scale platform on Databricks
citizenM is a hotel concept redefining hospitality through design and technology. Over six years, In2Intel built and evolved citizenM's entire data platform — scaling it alongside the company's growth from 12 to 38 hotels.
Overview
When we started with citizenM in 2019, their BI capability consisted of Power BI reports built on manual exports — only one system could be connected to directly. There was no reliable, central way to bring data from across the business together.
In2Intel built citizenM a data platform from the ground up: a SQL-based environment on Azure, with Azure Data Factory as the ETL layer. It gave the BI team a solid foundation to build on, and that team grew to 12–13 people. At its peak, the platform ran 26 integrations, spanning APIs, SQL/MySQL sources, file-based feeds (SFTP, storage accounts, VMs), BigQuery, and Google Analytics.
As citizenM grew — from around 12 hotels to 38 today — data volume and complexity grew with it. Website and app usage data in particular became too large and complex to process reliably in SQL. After first moving individual integrations to Databricks, In2Intel and citizenM decided to migrate the entire platform. The migration started in mid-2023 and was completed by the end of 2025. Today, citizenM's data platform runs on Databricks, with file-based storage in Unity Catalog structured around a medallion architecture.
With a reliable, scalable platform in place, citizenM could shift from gut feeling to data-driven decision-making — including personalized marketing based on RFM segmentation, and identifying cost savings across the business.
What we did
- Data Platform (Azure SQL + ADF)
- Data Warehouse
- Databricks Migration
- Unity Catalog & Medallion Architecture
When we started, citizenM had one system they could connect to directly — everything else was Power BI built on manual exports. Six years later we'd migrated their entire platform to Databricks, running two dozen-plus integrations for a BI team that had grown from nothing to more than a dozen people. Getting to build — and then rebuild — the same platform as the company itself grew from a dozen hotels to almost forty, that's a rare thing to be part of.
