Technical data

Redbird analytics operating system makes data more accessible to non-technical users TechCrunch

Data engineers have a big problem. Almost every team in their company needs access to analytics and other information that can be extracted from their data warehouses, but only a few have technical knowledge. Redbird was created to help everyone in an organization create and run analytics without using code, reducing the number of bottlenecks that data engineers have to deal with. The New York-based startup announced today that it has raised $7.6 million in an oversubscribed funding round led by B Capital, with participation from Y Combinator, Thomson Reuters Ventures, Alumni Ventures and Soma. Capital, as well as other funds and angel investors.

Redbird, formerly known as Cube Analytics, serves as an analytics operating system by connecting all of an organization’s data sources into a no-code environment that non-technical users can use to perform analytics, reports and other data science tasks. The new funding will be used to add more no-code capabilities. It also plans to expand its marketplace, where users and developers can exchange apps they create using Redbird.

Founded by data analytics experts Erin Tavgac and Deren Tavgac, Redbird works with leading companies across a wide range of verticals, including consumer packaged goods, manufacturing, retail, media and agencies. Erin previously worked at McKinsey, helping companies build and manage data analytics capabilities, while Deren was a product manager at Saks Fifth Avenue.

Erin told TechCrunch that the two quit their jobs to address enterprise data analytics issues such as lack of automation and advanced analytics that require coding skills. This means that data engineering teams cannot respond to all stakeholder requests, leaving companies unable to manage fragmented tools within a complex data stack.

Redbird solves these problems by allowing people without a technical background to create custom applications that automate analysis, removing bottlenecks for data engineering teams while giving everyone access to data analysis.

Redbird’s peers in the enterprise data analytics space include basic analytics tools like Tableau, Looker and Microsoft Power BI, which Tavgac said Redbird doesn’t consider direct competitors as they don’t automate complex end-to-end workflows, but rather provide generic data visualizations from datasets that have already been transformed.

A closer rival are advanced automation platforms like Alteryx, but it has a few drawbacks compared to Redbird. For one, it has less collection, data science and visualization capabilities, which means customers can’t use it as a full analytics workflow solution, Tavgac said. It’s also difficult for non-technical users to adopt, a problem Redbird was created to address.

Most of Redbird’s customers are large enterprises with over $1 billion in revenue. It is profitable, with seven-figure revenues and 9x revenue growth over the past year. Redbird monetizes through an enterprise SaaS model, with usage-based licensing fees.

Some examples of how customers have used Redbird: A large media company created automation workflows that collect data from over 10 sources, apply advanced analytics to it, and generate thousands of custom reports to guide their ad sales activities. A global CPG brand uses Redbird to digitally track brand health across a wide variety of data sources, like social media, e-commerce review, and Google search volume, and uses analytics advances to predict future sales trends.

In a statement, B Capital general partners Karen Page said, “We believe Redbird will become an essential platform for businesses to manage complex data workflows. This investment underscores our strategy of collaborating with innovative companies that enable rapid technological transformation in traditional industries.