data pipelines should not Be a problem for BI analysts Consolidated Modern Data Stack - Usable for BI Analysts Trusted worldwide by leading SMEs and startups Use pre-built templates that suit your data project Turn your E-Commerce into Zalando data drivenness
Measure effects across offline and online channels and allocate your budget.
Find out more > Equip your mobility startup with Uber like analytics
Merge the location data of your mobility startup with external data and predict demand.
Find out more > Perform location analytics like Starbucks does
Build for your retail or quick commerce startup a location model to predict revenue
Find out more > A Data Workspace for BI Analysts on top of the Modern Data Stack BI Analysts 📊 turn into Data Engineers
Cover end-to-end data use cases without coding.
Build complete analytics workflows through loading, transforming, and applying Get help by an engineer to customize your project whenever you need Use pre-defined templates for marketing, location, and startup use cases Discover templates Analytics Engineers 👩🏽💻 customize with tools they love
Stop writing redundant code and get rid of ad-hoc tasks
how it works Build reusable components for BI Analysts with the frameworks you love Add data sources with Airbyte, transformations with dbt, and new data science models with Python Kuwala is open-source with active community support Deliver your data project faster than expected ⚡️
With Kuwala we empower cross-functional teams to work efficiently with your data.
Consolidate your existing Modern Data Stack 🚀 No lock-in - Kuwala is extendable and open-source Solutions engineering with the Kuwala core team schedule a Call Espresso House builds a next gen location analytics system with Kuwala
Espresso House is a coffee shop brand with over 400 shops in the Nordics. They used Kuwala to merge internal and external data sources in order to train a model that informs the the expansion team of market potentials.
Standardization of multiple data sources providing POI and behavioral insights data Multi-layer data aggregation Frequent data update in order to keep the prediction model up to date “ Instead of only using empirical observations, we now take into account data from various sources in order to take data-driven decisions.” StephanieHead of Business Intelligence at Espresso House
For BI Analysts
Load any data source relevant to your business into Kuwala Pre-built transformations and models from our library
Built on top of the Modern Data Stack and your existing tools Extend any part of Kuwala with frameworks you love Choose a plan that suits your needs Community
All transformations Install via GitHub Support of the Kuwala community Join our community Cloud
Collaborate with multiple users on projects Pipeline management Hosted and maintained version with additional tech support Apply for beta Custom
Solutions engineering Prioritized integration requests Custom onboarding and training sessions free consulting Hour