Data Catalog

Due to rapid growth and diversity of data sources, data types, users and deployment models, organizations continue to struggle with manually identifying and inventorying distributed and heterogeneous data assets that deliver value.

However, with DQLabs augmented data catalog now allows full scan of existing data assets to derive end-to-end views of the data for governance and compliance. This not only allows the data stewards to discover metadata but also understand the data quality associated with each attribute.

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Data Catalog Features

Leverage DQLabs ML-augmented data catalog as a simplified metadata management to automate the process of discovering, inventorying, profiling and tagging.

Data Catalog Feature

Connect to all data sources and types

Discover and extract data catalog information from various enterprise data warehouses, operational databases, enterprise applications, cloud data stores, nonrelational data stores, and many more with few clicks using out-of-the-box connectors. We not only connect to the data sources but REST-based APIs , XMLs and PDFs but also automate profiling, clustering, indexing and creating of semantic relationships.

Data Catalog Feature

ML assisted Search and Querying

ML-assisted search and querying enables to perform semantic search over metadata to find the most relevant datasets and browse, filter these derived datasets as needed.

Data Catalog Feature

Understand Data Quality Impact

DQLabs provides data quality scoring with deep dive analysis on any attribute to perform or assess impact of usage in data preparation, reporting or analytics to ensure higher quality of reports, dashboards and ML models.

Data Catalog

Auto tagging and Classification

Includes classification per the most data privacy and security compliance regulations — such as the EU General Data Protection Regulation (GDPR) and California Consumer Privacy Act (CCPA) and sensitivity levels

Data Catalog Feature

Patent Pending DataSense™

With AI driven DataSense™ module, DQLabs modernizes the meta data, catalog and taxonomy management with an integrated AI/ML and automated rules and learning capabilities. Various tasks involved in data cataloging around metadata discovery, ingestion, translation, enrichment are automated via modern machine learning algorithms.

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Other Modules

All complex tasks around connection, data profiling, curation, master data management and reporting is all done in few clicks..

Data Quality

Ability to discover patterns, insights, fraud, missing values and correlations across attributes using all connected datasets and data sources within fraction of minutes using AI from users’ behaviors and automatic business rules configurations.

Data Curation

ML based smart curation modules to automatically curate the data based on the metadata definition and using Reinforcement Learning at all three levels of curation – Basic, Reference and Advanced.

Master Data Management

Easy entity definition and management of Master models and creation of master or golden key records for customers, products, devices, and other business entities.


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