Barcelona’s Qbeast secured €2.5M to make data lakes faster, cheaper, and easier

For its solution to make data lakes faster, cheaper, and easier, Barcelona-based Qbeast has just won a new pool of €2.5 million. Now, the company wants to quicken its go-to-market plan.

Elaia took the lead in the €2.5 million Seed round that was funded. Along with prior investors BStartup Banco Sabadell and business angels, new investors Sabadell Venture Capital and Uber Founding CTO Oscar Salazar and existing investor Inveready also took part.

We live in a data-driven society, and managing all that data is crucial for businesses across all industries. Data can be used to make predictions, provide insights into a company’s performance, and influence decisions.

Qbeast is a spin-off from the Barcelona Supercomputing Center – Centro Nacional de Supercomputación (BSC-CNS), intending to make it simpler to handle so-called data lakes and assist teams in making better predictions and optimizing operations. The startup recently received fresh funding as it prepares to enter the market.

To balance flexibility and effectiveness in data analytics, Cesare Cugnasco, Pol Santamaria, Paola Pardo, Clemens Jesche, and Nicolas Escartin founded Qbeast in 2020.

“Companies working with data have little choice: if they want to know what is occurring in their company, they need to use a data warehouse,” says Cesare Cugnasco, CEO of Qbeast. However, they require a data lake if they want to use machine learning to forecast the future and improve current processes.

Cesare added, “The result is that they use different technologies, require different personnel, incur double the cloud expense, and take twice as long to create. By facilitating the work of data teams and enhancing the effectiveness of data tools, Qbeast will alter this.”

The startup, which was created within the Barcelona Supercomputing Center, optimizes data organization to speed up and reduce the cost of engineering work while providing engineers greater insight, improved capacity to create data products, and the ability to train ML models at scale.

A community is growing around the open-source data lake format thanks to the Barcelona-based crew. Clod expenses and energy consumption can be reduced with quicker analytics and ML model training.

For instance, Qbeast claims that it has reduced the execution time of its data analytics for one of its clients by up to 50 times using sampling and by 68% with full precision, allowing faster analytics, cheaper cloud costs, and less energy use.

As of now, marketplaces, e-commerce platforms, IoT, and businesses from sectors like advertising & marketing, manufacturing, retail, and financial services are all showing interest in the young firm.

By filling important commercial roles and increasing investment in product development, technology, and alliances, the team will be able to accelerate the go-to-market.

Partner at Elaia Sébastien Lefebvre: “We are proud to support Qbeast and their incredibly talented staff, who are grounded in cutting-edge research. The founders are working to remove the obstacles that thousands of businesses face in utilizing data lakes effectively due to their perception of their perceived intricacy.”

“Qbeast has a lot of value to add, and we are excited to embark on this adventure together,” Sébastien continued.

Image Credit: Qbeast