Data governance company Collibra is acquiring OwlDQ, which uses predictive machine learning models to understand data quality. Collibra will integrate the vendor’s software into its existing cloud platform. With OwlDQ, Collibra plans to offer its enterprise users additional capabilities to centralize and automate their data quality workflows.
Collibra CPO Jim Cushman said in a press release that Collibra and OwlDQ will unify data governance, privacy, catalog, lineage, and quality with a single, cloud-based system.
Collibra uses a microservice architecture and open APIs. Its data intelligence cloud platform is agnostic, importing and automatically classifying data from sources such as OLTP databases, master repositories, and Excel files. It then analyzes the consolidated data and metadata with an enterprise user’s existing tools for business intelligence.
OwlDQ focuses on data quality. The software works to detect data anomalies, generate quality rules, and reconcile replication errors. Automated data quality measures can also help replace manual rule writing, which itself often requires code and a rules engine, and minimize any existing data silos in the process.
Once OwlDQ abstracts ingested data, it provides teams with an ML labeling system to down-train items on its platform. It applies rules afterward, using an adaptive approach that may save time for enterprises whose scale mandates more static rules than are feasible to write.
With the OwlDQ integration, Collibra may soon be better positioned against competitors like Informatica. Collibra plans to improve platform consistency and accuracy, allowing its users to create data-driven decisions with increased confidence.
Collibra was founded in Belgium in 2008 and has roughly 700 global employees. OwlDQ CEO Kirk Haslbeck will be joining them as Collibra’s new engineering VP. Today’s acquisition news also follows the company’s $112 million funding round in April 2020, when it announced a $2.3 billion total valuation, and its $100 million raise the year before.
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