Smart Data Curation

Identify the optimal data pre-processing strategies and automate your data curation with control on data quality thresholds.


With the explosion of data, and a variety of data integrations and sources, more and more companies are struggling with data cleansing, data curation or data wrangling– primarily the process of transforming and mapping data from one form to another.

DQLabs reduce operational costs and drive trustworthy outcomes using smart curated datasets using innovations in the area of AI/ML based algorithms and models.

Smart Data Curation Platform - DQLabs

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Data Curation Features

DQLabs AI/ML based smart curation modules identifies the optimal data preprocessing strategies and automates data curation with controls on data quality thresholds. This is further enhanced with the help of reinforcement learning and predicts the type of repair needed to resolve an inconsistency and applies to improve quality.

Generate More Accurate Data - Data Curation

Data Curation Features

Generate more accurate data

Using a careful blend of both unsupervised and supervised and ML algorithms, all unknown patterns in data are identified to cleanse and provide more highly accurate data

Data Curation Features

Multiple levels of data cleansing

Ability to deduplicate, clean and enrich data using three levels of curation – basic, reference and advanced algorithms. All of these are automatically configured based on the DataSense™ module of DQLabs

Multiple Levels of Data Cleansing - Data Curation
Inbuilt Continuous Learning - Data Curation

Data Curation Features

Inbuilt Continuous Learning

As market environments shift, so does business strategies and therefore the underlying data in the business operations. As the data evolves and takes new forms and different lifecycles, DQLabs learning platform continuously evolves and builds and removes rules automatically to improve the process of data cleansing.

Data Curation Features

Visual Learning with Detailed Curation Report

Visual Learning environment that allows business and technical users to interact with data and understand the root cause of quality issues. The platform comes with algorithms that are fine tuned to automatically discover patterns, insights, fraud, missing values and correlations across attributes, datasets and data sources within fraction of minutes to improve data quality.

Visual Learning with Detailed Curation Report - Data Curation
Human Guided or Human Curation for Reinforcement Learning - Data Curation

Data Curation Features

Human Guided or Human Curation for Reinforcement Learning

As business analyst or data stewards or data analyst interacts with DQLabs, the platform learns the user behavior from those interactions to guide and reinforce smart actions vs actions that further needs refinement. This combination of scaling the human element with ML algorithms helps us to cleanse vast amounts of data more effectively and smarter.

Data Curation Features

Transform by Configuration

Rather than authoring or creating heavy ETL / ELT workflows for cleansing the data, DQLabs provides an easy and intuitive way of configuring transform tasks to improve the consistency, validity, and reliability of the data.

Transform by Configuration - Data Curation
Standardize in Multiple Ways - Data Curation

Data Curation Features

Standardize in multiple ways

DQLabs standardizes automatically your data using multiple different algorithms sets but not only limited to Distance / Similarity / Phonetic based clustering, pattern detection, functions, or reference libraries.

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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 Catalog

DQLabs modernizes the meta data, catalog and taxonomy management with its out-of-the-box connectors and using its patent pending AI driven DataSense™ technology.

DQLabs' Modern Data Cataloging

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 Quality Management

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.

360 View or Golden View of Records
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