Collibra, the Data Intelligence company, today announced its “March to a Billion” initiative, a product journey designed to enable enterprises to load, discover, understand and use up to one billion assets with the Collibra Data Intelligence Cloud. The initiative is part of a series of product enhancements focused on performance at scale and data quality unveiled at Collibra’s Data Citizens ’21 conference.
In the wake of COVID-19, organizations are wrangling with growing volumes of data, complex data ecosystems, accelerated cloud migration and an urgent need for organization-wide collaboration. Collibra’s advancements provide customers a solution to these challenges and the benefit of a single, cloud-based platform to seamlessly leverage data resources throughout the enterprise.
“Across our customers and community of data citizens, we consistently hear that enterprises are hungry for a one-stop solution that delivers trusted data while simultaneously enabling access and visibility to metadata across the entire organization,” said Madan Gadde, chief customer officer at Collibra. “Our latest advancements ensure teams can go to one place to get everything they need to manage, trust and access their data resources while eliminating the complexity of integrating and maintaining relationships with multiple players.”
Balancing the Performance at Scale and Usability Tradeoff
Collibra has embarked on an anticipated two year “March to a Billion” journey, with the goal of allowing enterprises to load, discover, understand and use up to a billion technical metadata records. Internal baseline tests demonstrate the ability to manage more than 250 million technical and lineage metadata records, with incremental upgrades over the course of the next 18-24 months, which Collibra anticipates will enable the ability to load, manage and govern one billion assets.
“‘March to a Billion’ highlights Collibra’s latest innovation, upending traditional approaches,” said Jim Cushman, chief product officer at Collibra. “Competing solutions deliver performance at scale at the expense of usability – or vice-versa. Enterprises are left with a difficult choice: technology that focuses heavily on performance at scale and can process large amounts of data but offers little in the way of value-added services, or technology that is focused on usability but has hard limits as to how much data it can manage or where that data can be handled.”
Collibra believes that it is poised to avoid this tradeoff, enabling the enterprise’s data infrastructure to handle billions of pieces of information in production in a cloud-based environment, while ensuring the usability of that information.
Demonstrating the Integration of Data Quality
Following its recent acquisition of predictive data quality provider OwlDQ, Collibra is integrating data quality into its Data Intelligence Cloud and leveraging its approach to solving the inefficient, error-prone, labor-intensive process of writing logic rules.
Collibra’s continuous and autonomous data quality solution automatically generates between 60-70% of rules – eliminating human error and the costs associated with manual labor, while continuously evaluating and adjusting to the inevitable data changes.
“With the additional capabilities of data quality and performance at scale, our Data Intelligence Cloud is providing a comprehensive suite of capabilities that are highly complementary,” said Cushman. “It’s rare that you have data quality without data governance and privacy, so why should you always have to integrate it and manage two different vendors that might not be aligned? These integrations further our ability to deliver maximum efficiency, flexibility, quality and performance to our customers.”
Learn more about the Collibra Data Intelligence Cloud.
About Collibra
Collibra helps our customers do more with trusted data. Our Data Intelligence Platform brings flexible governance, continuous quality and built-in privacy to the world’s leading brands. To learn more, visit collibra.com and follow us on LinkedIn, X, Facebook and Instagram.