Fast, Reliable, and Scalable

Trusted By Modern Data Teams Worldwide

Observe-Measure-Discover

the data that matters
The DQLabs platform harnesses the combined power of Data Observability, Data Quality and Data Discovery to enable data producers, consumers, and leaders to turn data into action faster, easier, and more collaboratively

Get alerted automatically for any deviations from known benchmarks to identify unknown issues at data in rest and motion

Agile quality-focused assessment for known issues across domains for data leaders, producers, and consumers

Automatic identification and classification of business terms across your data for standardized quality checks and improved governance

Unified Data Quality Approach

With the growth in data and the varying needs of data engineers, data scientists, and analysts, you need a simple, augmented data quality platform that monitors and measures quality in different ways they see the data relevant to their roles

Improve data trustworthiness for critical decisions using automated data monitoring

Improve confidence in consumption using outcome-focused checks across processes

Auto discover rules using centralized management of reference and business terms

Modernize your data infrastructure in minutes using ML-powered, no-code data quality checks

Deliver millions of checks across petabytes of data across lakes and warehouses in seconds

SOC Type 2 compliant platform in a highly secure infrastructure with no customer data retrieval

The State of Data Observability

Did you know that over 80% of organizations rely on quality data to make decisions? However, if this data is not reliable, a company can quickly make the wrong calls
Data observability is one of the most important topics in data engineering today
But what is it, and why do you need it? In this post, we’ll…

Data Observability is Irrelevant without Context

With today’s rapid growth in data, a focus towards data quality is more critical than ever before
Since the first bit of digital data existed Data Quality has existed alongside it as a practice, and yet after decades gaps in the marketplace still exist as the focus towards business impact is often forgotten
We quite…

The Noise in Modern Data Quality

The need for high-quality, trustworthy data in our world will never go away
With the growth in data, the need arises more than ever before
Even though we have evolved from data silos to pipelines (ELT/TL) to streaming to modern data stack/warehouse, multi-cloud, data mesh — still we are faced with an age-old problem of…

Gartner Data Quality Software Comparison – DQLabs Rated High

Gartner, Inc
just released a comprehensive comparison of the leading suppliers of Data Quality Software which included DQLabs
The Connecticut-based technology research and consulting company published this report covering data management solutions for technical professionals
Gartner undertook this study after surveys with leading organizations revealed that capabilities provided by traditional data quality software require too…
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