Deeper Integration with the Microsoft Ecosystem Makes Cube Cloud the Best Universal Semantic Layer for Microsoft Enterprises
Cube, providers of the leading universal semantic layer platform, announced expanded integrations with Microsoft Power BI and Microsoft Excel to support enterprise data and analytics teams leveraging the breadth and flexibility of the Microsoft analytics suite.
“Enterprises are rapidly adopting cloud data platforms like Microsoft Azure, Snowflake, and Databricks,” said Artyom Keydunov, CEO and Co-Founder of Cube. “However, the shift to the cloud has left many organizations without a modern OLAP solution for multidimensional analysis that can integrate with a broad ecosystem of data consumption tools. We are excited to announce our native integrations with Excel and Power BI. With our new DAX API, enterprises can query data live, without extracts, in cloud data warehouses, such as Snowflake and Databricks, directly from Power BI.”
Also Read: Astronomer Releases Astro Observe for Data Visibility
Cube is introducing two critical enhancements to its Microsoft ecosystem integrations:
- Data Analysis Expressions (DAX) API for Power BI: This new integration enables users to connect natively from Power BI to Cube and query Cube data models in real-time using the DAX API. This architecture enables direct access to live data in cloud data warehouses, such as Databricks and Snowflake, from Power BI, while retaining all the power and expressiveness of the DAX query language.
- Cube Cloud for Excel Add-in: The Cube Cloud for Excel Add-in connects to governed data with Excel desktop or Excel online. Users can slice, dice, and pivot using a custom interface and update their analyses from the data source in one click. Instead of relying on manual data exports or snapshots to perform multidimensional analysis, leading to outdated insights, inefficiencies, and a lack of governance, Cube‘s MDX API and Excel Add-in restore and modernize these capabilities by enabling direct, live connections to governed cloud datasets.
Source: PRNewswire