Kongsberg Digital achieves 60% cost reduction and real-time data refresh with Databricks
Norwegian industrial SaaS provider Kongsberg Digital modernized its data warehouse on Databricks, increasing data refresh frequency from four times daily to hourly (a 300% increase) and cutting data processing costs by 60%.
Overview
Norwegian industrial SaaS provider Kongsberg Digital modernized its data warehouse on Databricks, increasing data refresh frequency from four times daily to hourly (a 300% increase) and cutting data processing costs by 60%.
This entry has 14 published fields tied to exact passages in an immutable source capture.
Inspect the highlighted sourceThe challenge
Kongsberg Digital's legacy on-premises data warehouse, and an initial cloud migration to Azure Data Factory and Azure SQL, was costly and limited in scalability, and the company needed to increase the frequency of data refreshes to give teams near real-time insights while keeping costs manageable.
The solution
Kongsberg Digital implemented Databricks as the core of its new business data platform, using optimized workflows and reduced compute demands compared with its previous solution, and standardized templates and CI/CD pipelines to onboard new team members.
Reported business value
Kongsberg Digital improved its data refresh rate from four times per day to every hour, a 300% increase in frequency, and realized a 60% reduction in data processing costs.
Sources
Open any source and check the claim yourself — that is the point of the register.
This record was researched and written with AI assistance, and its claims were checked against the sources above. (EU AI Act art. 50 transparency notice.)
Other technology & software entries in the register.
HP crafts marketing campaigns that resonate with customers using Databricks and Uniphore
HP centralized first-party customer data on the Databricks Data + AI Platform with Delta Lake and Unity Catalog, and connected it to Uniphore's HybridCompute for federated query pushdown, cutting campaign setup from 2 weeks to 2 hours and processing 400 million records in seconds.
Building a safer and more sustainable world
Novade, a construction management software company, partnered with Databricks to modernize its analytics and ML infrastructure, moving from a homegrown Apache Airflow stack to the Databricks Data + AI Platform with Delta Lake, Unity Catalog and MLflow. The move reduced total cost of ownership by 60% and supported a 100% increase in new clients, while enabling ML models for predicting incident risk affecting worker safety and project delivery schedules.
SafeGraph optimizes geospatial data processing with Databricks and Delta Sharing
SafeGraph used the Databricks Data + AI Platform, Delta Lake, Delta Sharing and MLflow to process petabytes of geospatial data and feed predictive models, achieving 2x-10x faster spatial querying, indexing and partitioning and a 50% reduction in peak memory consumption compared to other platforms, while reducing data access time for partners from months to minutes via Delta Sharing.
Transforming Weather Forecasting with Lakeflow Jobs
AccuWeather migrated from on-premises infrastructure to Databricks and Lakeflow Jobs, working with Datadog for observability, to unify diverse weather data formats and orchestrate 4,500+ weekly jobs. Lakeflow Jobs coordinates the ingestion of multiple weather models, triggers machine learning processes that weight and blend different forecasts, and manages complex job dependencies for reinforcement training workflows used in AccuWeather's proprietary forecasting engine. AccuWeather reports 3x faster dataset development (three months to one month per dataset), a 50% reduction in unactionable alerts, and 50% cost savings on serverless job usage.
AccuWeatherLakeflow Jobs · Delta Sharing · DatadogWas this helpful?
Your feedback helps us improve our use case database