I’m excited to announce that Cube and Coalesce have entered into a strategic partnership to better support joint customers in building powerful and easy to manage data platforms. Coalesce, the data transformation company, and Cube, a leading universal semantic layer platform, are natural complements for each other. We are both built-in-the-cloud technologies with a strong developer-centric philosophy. We’re both highly scalable with deep ecosystem integrations. Coalesce is well-known within the Snowflake ecosystem and Snowflake is the most common data source used with Cube Cloud.
Data transformation technologies, sometimes known as ETL, or ELT tools, are one of the most important parts of enterprise data architectures. These technologies help automate movement of data from source systems to cloud data warehouses, lakehouses and other databases and perform the transformation steps necessary to make data useful.
Coalesce is a shining example of a data transformation platform with an easy to understand interface that helps developers quickly automate common transformation tasks and makes implementing common data modeling patterns like star schemas simple. It’s a great solution to save developer time and reduce errors and as a former data architect it’s been a joy to learn.
How Coalesce and Cube Work Together
Transformation is important to a universal semantic layer like Cube, because it represents the major data handling step before Cube in common data platform architectures. Cube and Coalesce are neighbors who share the cloud data platform Snowflake as a common point of exchange.
Organizations load their raw data into Snowflake, transform it with Coalesce, and when they are satisfied, connect to it with Cube's universal semantic layer. Cube then takes over, with users defining their dimensions, measures and metrics that will be exposed to downstream applications. These metrics are then exposed through our long list of API endpoints and integrations. This pair of transformation and semantic modeling supports the data lifecycle from raw data to refined, governed and trusted business metrics.
Using Cube and Coalesce together makes it easy for developers to trace the complete path of data from their source systems all the way to their data applications, business intelligence tools, spreadsheets and AI use cases. Coalesce provides built-in column lineage features to understand the impact of altering a transformation on downstream models. Cube provides cataloging and lineage features to understand the path that semantic modeled data takes from Cube to downstream applications. By combining these features, users can make changes to their data model, whether in the transformation layer, or the semantic layer with confidence.
Learn More About Cube and Coalesce’s Strategic Partnership
With Cube and Coalesce, developers can go all the way from raw data to business-ready metrics while using both tools to automate much of the heavy lifting of writing complex SQL. If you’d like to learn more about the strategic partnership between Cube and Coalesce you can check out the following resources:
- Cube co-founders Artyom Keydunov and Pavel Tiunov will be appearing on Coffee with Coalesce: Semantic Layer Innovation with Cube on October 17th.
- Tony Kau will appear on Demos with Doug: Peeling Back Semantic Layers with Coalesce and Cube to demonstrate our integration with Coalesce on November 13th.
- There is also a great write up about our integration on the Coalesce website, Achieve Data Maturity With an Integrated Semantic Layer.