InfoBluePrint has partnered with DQLabs.ai, the leading innovator providing an augmented data quality platform for enterprises to manage data smarter and leverage an immediate ROI. DQLabs, with a Data Quality First approach, helps organisations connect, discover, measure, monitor, remediate and improve data quality across any type of data – all in one agile and innovative self-service platform!
The result? Data unification and improved collaboration and governance to help you discover, trust and consume data at ease.
DQLabs uses innovative AI decisioning in data management and provides a single comprehensive platform that learns and adapts to your specific data culture. The DQLabs platform not only re-aligns as business strategy shifts, but also provides the ability to pinpoint the root-cause of issues to the source with self-service capabilities.
DQLab’s partnership with InfoBluePrint allows us to provide your organisation with both a cutting-edge data management product and data quality implementation services for a 360-degree solution that helps increase revenue through managing your entire Data Quality Life Cycle.
You will enjoy a modern stack DQ tool that goes beyond simple data observability. DQLab is built on Spark/Databricks, Python Django and Postgres and is truly unique in its use of Artificial Intelligence/Machine Learning to self-learn and auto-classify attributes and rule applications – leading to what is now called “Augmented Data Quality” by Gartner. It has innovative features such as Automated Semantics Discovery, Auto-tagging, Automatic Rules Identification, Auto PII Sensitivity Classification and associated Data Masking.
1. Smart Connectors
Connect to unlimited data sources in any form, shape or location
2. Semantic Discovery
Auto-discover rules by semantic identification and classification
3. Measure Data Quality
Evaluation of all attributes across subjective and objective data quality rules & dimensions
4. Monitor Drift & Behaviour Analysis Continuous DQ monitoring using different types of anomaly detections across for example length, pattern, null and blank
5. Remediate & Improve Data Quality
Remediate Data Quality Issues by cleaning, enriching and merging good records using ML-based Smart Curation and Self Learning
6. Business Dashboards & Insights
Outcome-focused measurement using KPI metrics and performance dashboards
For more information on the DQLab product visit: https://www.dqlabs.ai.
Let InfoBluePrint help you fast-track your Data Quality project, both architecturally and programmatically - helping you to plan, design and build a successful and sustainable Data Quality and MDM solution.
Need to discover how we can help your organisation implement DQLabs? Please get in touch:
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