Modern cloud data warehouses lack the capability to direct query Excel, making cloud migration difficult for organizations needing to support Excel workflows.
Cube solves this problem by creating a multidimensional layer with semantic models on top of tabular data in cloud data warehouses, allowing Excel users to maintain familiar multidimensional pivot table workflows.
A new wave of tools is being built specifically for embedded analytics solutions, so we wrote a quick blog about how some of these tools fit together and why they are such great choices.
Semantic layers and metrics stores play a pivotal role in the world of data analysis. They act as bridges between raw data and actionable insights, enabling organizations to harness the full potential of their data. A semantic layer, in particular, consolidates complex data into a format that is understandable across different teams and tools, effectively translating raw data into common business terms.
Cube solves this problem by creating a multidimensional layer with semantic models on top of tabular data in cloud data warehouses, allowing Excel users to maintain familiar multidimensional pivot table workflows.