Artificial Intelligence | News | Insights | AiThority
[bsfp-cryptocurrency style=”widget-18″ align=”marquee” columns=”6″ coins=”selected” coins-count=”6″ coins-selected=”BTC,ETH,XRP,LTC,EOS,ADA,XLM,NEO,LTC,EOS,XEM,DASH,USDT,BNB,QTUM,XVG,ONT,ZEC,STEEM” currency=”USD” title=”Cryptocurrency Widget” show_title=”0″ icon=”” scheme=”light” bs-show-desktop=”1″ bs-show-tablet=”1″ bs-show-phone=”1″ custom-css-class=”” custom-id=”” css=”.vc_custom_1523079266073{margin-bottom: 0px !important;padding-top: 0px !important;padding-bottom: 0px !important;}”]

Collibra Acquires Predictive Data Quality Vendor OwlDQ

Collibra, the Data Intelligence company, announced the acquisition of OwlDQ, a leading provider of predictive data quality software.

OwlDQ uses machine learning to detect anomalies in data, to generate data quality rules automatically and to reconcile replication errors. The company helps leading organizations like Constellation and VillageCare make their data cleaner every day. The integration of OwlDQ into the Collibra Data Intelligence Cloud introduces a new offering, Collibra Data Quality, which will allow organizations to centralize and automate data quality workflows to comply with global regulations and streamline their data and analytics processes across the enterprise.

Recommended AI News: Banjo Health Inc. Announces Partnership with ELMCRx Solutions

“Data quality is integral to Data Intelligence, and poor data quality is a key reason why organizations don’t trust their data,” said Jim Cushman, chief product officer for Collibra. “Together, Collibra and OwlDQ will provide organizations with a single, cloud-based system of engagement to unify data governance, data privacy, data catalog, data lineage and now continuous data quality so teams can more easily and confidently get to trusted business insights and become data informed.”

Related Posts
1 of 40,386

Many companies lack the enterprise data quality foundation necessary to respond to regulatory and business analytics demands in a scalable way. Without one, organizations are often trapped in manual rule writing and management, limited data connectivity, and a siloed view of data quality. This can result in massive productivity loss and costly fines due to regulatory risk and non-compliance, along with significant potential revenue loss.

Recommended AI News: Server at Work Rebrands as SAW.IT

“We’ve developed some of the most advanced machine learning to address comprehensive data quality challenges, such as profiling, rules, data reconciliation and discovering hidden data relationships. With OwlDQ’s predictive data quality, companies can reduce complex and error-prone manual rule writing, streamline their data and analytics processes and expedite trusted business outcomes,” said Kirk Haslbeck, founder and CEO of OwlDQ, who will serve as vice president of engineering at Collibra. “We are so excited to bring OwlDQ together with the Collibra Data Intelligence Cloud to provide a unified, scalable solution across diverse databases, files and streams with continuous and comprehensive self-service data quality through ML-powered, auto-discovered and adaptive data quality rules.”

Recommended AI News: InGen Dynamics to Continue to Diversify Application of A.I and Robotics Technologies

2 Comments
  1. Electrolytic copper refining says

    Scrap Copper certification Copper scrap contracts Metal scrap storage
    Copper cable recycling best practices, Metal reclamation and reutilization solutions, Copper scrap export permit

  2. Scrap metal baling services Ferrous material contamination prevention Iron scrap management services

    Ferrous material sourcing, Iron reclamation solutions, Scrap metal disposal regulations

Leave A Reply

Your email address will not be published.