Out of the Box Data Quality Scoring for Snowflake

DQLabs.ai and Snowflake partnership enables out of the box data quality scoring , observability enabled with augmented data discovery as one single agile platform with self-learning and self-service features for Snowflake customers. Just connect and monitor data across all your snowflake data warehouse for data quality issues and remediation in minutes.

DQLabs leverages the new world of AI decisioning in data management and provides Snowflake users with a single comprehensive platform that learns, adapts to your specific data culture. With the use of AI/ML, decisioning is made possible in all aspects of data management and provides organizations a smarter way to manage data.

With higher degree of automation, both business and technical stakeholders can improve ROI and enrich customer experiences by discovering trustable data and business insights in minutes.

Key Values of the DQLabs + Snowflake Partnership

Connect + Discover
Measure + Monitor
Remediate + Enrich
Insights + Recommendations

Snowflake Native Connector

Snowflake certified native connector which seamlessly connects to the Snowflake Data Cloud with secured scan or pull options for profiling and data quality or observability use cases.

Snowflake Native Connector - DQLabs
Semantic Discovery - DQLabs

Semantic Discovery

Automatically harvest technical meta data, patterns, catalog, discover data quality rules by semantic identification and classification of sensitive data in Snowflake.

Profile and Measure Data Quality

With advanced Datasets or Query mode feature users can select and refine specific Snowflake schema, table or critical data elements for subjective and objective data quality dimensions.

Profile and Measure Data Quality - DQLabs
Monitor Drift and Behavior Analysis - DQLabs

Monitor Drift and Behavior Analysis

Deploy Adaptive Threshold based Continuous DQ monitoring for Snowflake using different types of anomaly detections across length, pattern, nulls, blanks, monitor duplicates and schema level changes, detect irregularities in your data loads including changes in data volume along with changes in data characteristics to identify outliers.

Remediate and Improve Data Quality

Leverage DQLabs for Snowflake and Remediate Data Quality issues by cleaning, enriching, and merging good records using ML based multi-level Smart Curation and Self Learning feature which continuously learns from every user interaction.

Remediate and Improve Data Quality - DQLabs
Business Dashboards and Insights - DQLabs

Business Dashboards and Insights

DQLabs enables leaders and functional managers to create and customize their own dashboards derive Insights and actionable recommendations in just a few clicks using smart widgets which helps them make sense of the data in their own ways.

Best Practices

DQLabs in Action: Observe, Measure, Discover


DQLabs in Action: Observe, Measure, Discover

The Modern Data Stack needs Modern Data Quality. Organizations deserve a better way to observe, measure and discover the data that matters. It’s time we eliminate the data silos created by legacy Data Observability, Data Quality and Data Discovery platforms by centralizing them into a single, agile solution. That is Modern Data Quality. That is DQLabs.

Join us on this webinar to learn how the DQLabs platform is the Modern Data Quality Platform eliminates critical data silos by centralizing Data Observability, Data Quality, and Data Discovery into a single, agile AI-driven platform.


12:00 pm: Welcome & Introductions

12:05: pm: Industry Insights: Defining Modern Data Quality

12:15 pm: DQLabs in Action: Platform Showcase 

12:30 pm: Questions & Answers

12:45 pm: Close

View More Arrow image