OwlDQ

Provides a data quality and observability platform that uses machine learning to automatically generate and adapt data monitoring rules, reducing the need for manual rule creation. It identifies and remediates data quality issues in real time, ensuring accurate, consistent, and compliant data across enterprise systems.

Traction 10/10

McLean, United States · HQ

Founded 20171K

Artificial Intelligence
Data & Analytics
Enterprise Software
Software Only

Updated 5 months ago

Funding

Funding rounds are not available yet.

Founders

2 founders

Felix Van de Maele

Co-Founder/CEO

Stijn Christiaens

Co-Founder

Product

Problem

Organizations struggle to maintain data quality across diverse systems due to the manual effort required to create and adapt data monitoring rules. This often leads to inaccurate, inconsistent, and non-compliant data, resulting in increased operational costs and flawed business decisions.

Solution

Collibra Data Quality & Observability provides a data intelligence platform that automates data monitoring and anomaly detection using machine learning. The platform automatically generates and adapts data quality rules, reducing the need for manual configuration. It connects to various data sources, including cloud platforms and databases, and scans data where it resides using pushdown or pull-up processing. By identifying and remediating data quality issues in real time, the platform ensures that data is accurate, consistent, and compliant across the enterprise. The platform also provides features for data classification, schema change detection, and data pipeline health monitoring.

Target Audience

The primary target audience includes data engineers, data stewards, data governance teams, and other data professionals who need to ensure data quality and reliability across their organizations.

Features

AI-powered AdaptiveRules that automatically generate and adjust to changing data conditions
Automated data classification using industry-specific rules for enforcement of data quality
Generative AI for writing complex data quality rules using natural language prompts
Data pipeline health monitoring to identify blind spots in data operations
Schema change detection to prevent issues on dashboards and reports
Pushdown and pull-up processing for efficient data scanning
Connectors to over 40 databases and file systems