“Headless” connector makes consistent data available to every data consumer in a company, no matter which applications they use
Cube Dev, the open source company behind the Cube headless BI platform, announced an updated API that makes its consistent data definitions accessible to users of every major business intelligence application.
Thousands of companies from startups to Fortune 500 enterprises have built data stacks that use cloud data warehouses for data storage, Cube for accessing this data and defining data models, and open source front-end tools for data visualization. This stack has enabled an ecosystem of custom data applications and analytics features embedded in mobile and desktop apps.
However, a much larger number of businesses use business intelligence applications and dashboard tools to summarize the data they collect and store, with the global market for these applications exceeding $25bn USD in 2022.1
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“Data needs to be consistent and performant not just for developers but also for analysts and general business users. This requires bringing Cube into the tools where these users already work.”
“It has always been our ambition to make Cube’s power accessible to a great diversity of data consumers,” said Artyom Keydunov, Cube Dev’s Chief Executive Officer and co-founder. “Data needs to be consistent and performant not just for developers but also for analysts and general business users. This requires bringing Cube into the tools where these users already work.”
Today’s launch of a PostgreSQL interface to the Cube platform makes it possible for BI tools such as Tableau, Superset and Microsoft Power BI to query Cube as a data source. This means that these tools consume the same definitions and data as custom applications and embedded analytics features that use Cube’s GraphQL and REST interfaces.
Don’t-Repeat-Yourself Design for Consistency and Performance
Without a headless BI solution, businesses must configure each data application their employees use to connect directly to data sources. This results in duplicated effort, inconsistent security and slow performance.
If a specific BI application is used to define business metrics—for example, defining which transactions should be summed to equal “total sales”—those definitions are not reusable by other applications. When the teams within an enterprise use different tools to re-create definitions, the definitions may conflict.
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By contrast, an organization can configure Cube—once—to securely access data sources, define data models, powerfully cache queries and make data available to every application, including BI tools. This results in the same data being accessible to every data consumer in a company, no matter which end applications they use. “Total sales” will mean the same thing in executives’ dashboards, marketers’ campaign reports and a finance team’s revenue models.
By abstracting away complex queries of raw data sources, Cube additionally reduces the difficulty of exploring data with collaborative data tools and notebooks. “We’re enabling companies to do more with the data they’ve stored,” Keydunov said.