Databricks SQL
12 use cases using this technology
Operationalizing Analytics Data at Scale (DEICHMANN SE)
DEICHMANN SE
DEICHMANN SE, Europe's largest footwear retailer with roughly 4,700 stores in more than 30 countries and about 8.7 billion euros in 2024 revenue, adopted Databricks Lakebase, a managed PostgreSQL database integrated with its Databricks Lakehouse, to activate governed customer and product data for e-commerce marketing without building separate integration pipelines. Lakebase reduced a data-product publishing pipeline to 3 clicks and about 30 seconds, and is now in production across Europe feeding SAP Emarsys for e-commerce marketing.
Trackunit Builds IrisX on Databricks, Giving Construction Customers 5x Faster Time-to-Market
Trackunit
Construction telematics company Trackunit unified previously siloed Finance, Engineering and RevOps data (6 million connected machines, 3 billion data points processed daily) onto the Databricks Data + AI Platform, then exposed that capability to customers through its IrisX platform. OEMs, rental and construction companies building on IrisX see 5x faster time-to-market than building their own data architecture, and Trackunit is extending the platform toward predictive maintenance using Databricks Genie and Agent Bricks.
Plenitude builds machine learning models on Databricks to forecast energy demand and renewable production
Plenitude
Eni-owned energy company Plenitude, which serves 10 million households and businesses across Europe, uses statistical models and machine learning on the Databricks Data + AI Platform to forecast customer energy consumption at hourly and daily granularity, forecast wind and solar generation from its renewable asset portfolio, and run customer segmentation and propensity models across 60 implemented use cases.
Maya is simplifying banking for diverse populations
Maya
Maya, the Philippines' leading fintech company, partnered with Databricks to modernize its data architecture into a unified lakehouse on Delta Lake, centralizing 100% of its data for real-time access and AI scalability. Maya's ML-powered underwriting tools cumulatively disbursed $2.1 billion in loans by year-end 2024. AI-driven fraud detection, combining transactional sequence embedding, network analysis and predictive modeling, achieved up to a 98% reduction in fraud losses. Hyperpersonalized, AI-driven marketing campaigns increased average revenue per user (ARPU) by 45%. Using Unity Catalog for governance and automated ETL pipelines, Maya also achieved a 28% increase in storage capacity without a rise in costs.
GoGuardian: Safer schools, empowered teachers, thriving students
GoGuardian
GoGuardian, which powers safe, focused learning for half of U.S. K-12 students, migrated its ML infrastructure to Databricks to manage billions of daily inferences for web filtering, classroom management and harm prevention while maintaining a PII-free, COPPA/FERPA-compliant data environment. Using Delta Lake, Lakeflow, Unity Catalog, MLflow and Databricks Model Serving, GoGuardian achieved up to 50% reduction in machine learning operational costs, 90% operational cost savings with its Delphi website classification model, and a 62% reduction in inappropriate device use among students. AI-driven prioritization also cut the volume of records requiring human review for high-risk content by over 95%, from 1 million to 35,000-45,000.
TBC Bank Operationalizes Trusted Data with Lakebase
TBC Bank
TBC Bank, the largest banking group in the Caucasus region, built a Lakehouse on Databricks and adopted Lakebase and Databricks Apps to move from on-premises SQL Server instances and month-long reporting cycles to self-service analytics and AI-driven applications, including a web-based AI chatbot and AutoML-based credit risk scoring. Credit risk model deployment fell from 14 weeks to two days, and more than 600 users regularly query governed data through Genie.
NOL UNIVERSE builds unified data lakehouse with Databricks, cutting batch computing costs by 77%
NOL UNIVERSE
NOL UNIVERSE, a Korean travel, leisure, and culture platform operating the NOL, NOL Interpark Tours, and NOL Tickets brands, migrated approximately 2,500 Hive-based queries and its Apache Airflow/NiFi pipelines to the Databricks Platform, consolidating disparate BI tools into a single environment and giving each business domain a self-service analytics environment governed by Unity Catalog. The customer service team also used Databricks machine learning to automate categorization of CS consultation history. The migration was completed in two months, reducing time to complete batch aggregation by 66%, decreasing batch computing costs by 77%, and increasing data availability time by 27%.
Illimity modernizes commercial banking with Databricks and adopts LLMs for customer-centric chatbots
Illimity Bank
Illimity, an Italian digital bank, built its data architecture entirely around the Databricks Data + AI Platform to process data in real time, extract actionable insights and securely share it with partners. Databricks has supported Illimity's adoption of LLMs, using vector embedding and vector databases, to inform its knowledge base and power intelligent customer-centric chatbots. Illimity is also exploring Databricks Clean Rooms to monetize its architecture using deterministic or machine learning models without compromising confidentiality.
E.ON Powers Better Decision-Making with Databricks Apps
E.ON
E.ON, one of Europe's largest energy companies, used Databricks Apps to deploy internal BI applications in one to two minutes. E.ON is working on analyzing 500-600 public ChargePoint operator contracts using a GenAI-powered chatbot that extracts contract details such as pricing and tariffs via natural language queries. Interactive dashboards built with Databricks Apps give E.ON's health and safety team real-time incident data and insights, including maps of incident locations and weather conditions, to identify patterns and mitigate risk in high-voltage field work. 1,500 employees now rely on Databricks for BI dashboards and insights.
Techcombank: Ushering Personalized Banking for Millions of Customers
Techcombank
Techcombank, Vietnam's largest private financial institution with 315 branches serving over 15.3 million customers, adopted the Databricks Data + AI Platform to unify data from disparate on-premises databases and a legacy data warehouse. Central to the initiative is 'Customer Brain,' a customer-360 tool centralizing customer data for targeted marketing, and the Lead Allocation Curated Engine (LACE), which uses AI insights to prioritize and assign sales leads. Techcombank built machine learning models for fraud detection and credit risk management, using an enterprise feature store with over 7,500 features and more than 100 ML risk models to manage a credit lifecycle handling a twentyfold increase in retail credit applications. MLOps on Databricks with MLflow cut model implementation from months to weeks. The bank is developing an internal RAG-based chatbot, Smartie, built on Databricks AI Search, and piloting AI/BI Genie for natural-language data queries. The platform has over 1,000 active users bank-wide.
TMAP Mobility Powers Smarter, Safer Travel
TMAP Mobility
TMAP Mobility, Korea's leading mobile navigation service with over 25 million subscribers and adoption in more than 95% of domestic vehicles, adopted the Databricks Platform to address data access and governance roadblocks that stalled AI-driven personalization efforts. Using Genie Space, non-data specialists can now explore and analyze data with natural language, and Unity Catalog provides granular permission management and column masking. As of September 2025, the analytics team receives 68% fewer simple data extraction requests, and approximately 48% of all employees can directly explore and utilize data. TMAP processes more than 7.3 billion mobility data points annually and used the Recommendation Engines Solution Accelerator to prototype and deploy scalable recommendation models faster.
Lippert Improves Customer Support with GenAI
Lippert
Lippert, a $3.8 billion global manufacturer of components for RV, marine and automotive brands, used Databricks and Agent Bricks to consolidate fragmented data into a single lakehouse and deploy AI agents for customer support. An AI assistant trained on product manuals, technical case history and field-expert videos surfaces troubleshooting guidance for call center agents in real time, cutting new-agent ramp time from six months to four weeks (an 85% reduction). Using Agent Bricks' evaluation framework and synthetic data, model accuracy for the support agent improved from 33% to 84% within weeks. AI also analyzes thousands of support calls daily for coaching and quality scoring (versus a prior manual sample of 100 calls/month) and automates call summarization into Salesforce. The initiative is expected to save millions per year and reclaim hundreds of thousands of hours, with new agents planned for HR, warranty and supply chain.