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About Us

We understood everyone preaches Data Quality however don’t have an out of the box platform for an end-to-end data quality across both business and technical users. Bad data will never go away but understanding and fixing where possible using automation is much more important with growth in data.

The efforts spent towards traditional rules based DQ measurement haven’t scaled and newer thought process such as observability without the lack of semantics or business context results in more false positives than being useful. The net result is that organizations spent time and money without any value generation.

Data Quality First

With growing data and modern data management, it was time to pragmatically shift away from traditional ways and move into a new way of “Data Quality First” approach.

Self Learning

Semantics (business context) based automated Data Quality measurement and monitoring

Self Service 100% DQ Automation

Automate as much as possible but with relevance and self-learning capabilities

Enables all types of users

Serve all type of users – Business (Data Quality Stewards, Catalog, Governance) and technical (DataOps, Data Scientist, DevOps, Data Engineers etc.,)

An approach that works for all types of users – business and technical. That’s what we did. We worked with various clients to understand the challenges across various ecosystems, users, different maturity life cycle and built a platform with three guiding principles in mind. Over the next year, we did various deployments and solution accelerators across a wide variety of verticals and enhanced the platform to be more stable, provide immediate ROI and more importantly user friendly, self-learning as it goes to adapt to your unique organization needs.

As a result, today you get to enjoy an Out of the box Actionable Data Quality Platform for all needs.

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Best Practices

EVENTS

Out of the Box Data Quality Scoring for Snowflake

In this webinar, let’s jump into the next generation of data management by using an augmented data platform with automated data discovery and data quality – all out of the box.

As part of this session, Raj Joseph, CEO of DQLabs shall present a demo of DQLabs.ai and demonstrate how you can make all of your data assets on Snowflake and other sources instantly discovered and searchable with ready-made Data Quality measurement and monitoring –automated to reduce your Time to Value.

Webinar Highlights

A thorough overview of the Modern Data Stack and where Snowflake with DQLabs fits in.
Learn how you can leverage augmented technologies to manage your modern data stack.
A demonstration of the DQLabs.ai AI/ML augmented data platform with specific use cases around off the shelf data discovery and data quality.