dqlabs
Observe and manage the health of your data ecosystem with no-code advanced anomaly detection algorithms.
Identify missing data before it impacts your projects and models.
Modern-day systems are fast transforming into complex, open-source, cloud-native microservices running on Kubernetes clusters. What’s more, they are being developed…
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Defining Data Observability and Data Quality As companies gather seemingly endless data streams from an increasing number of sources, they…
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With today’s rapid growth in data, a focus towards data quality is more critical than ever before. Since the first…
Read MoreLeverage DQLabs’ unified platform with smart capabilities across data observability, quality, and discovery.
Using DQLabs smart connectors that comes out of the box, you can connect to an unlimited amount of data sources in any form, shape and any location.
With DQLabs’ Data Sense™ capabilities, you can automatically enrich semantics for any type of data with or without metadata information.
Scan various types of data sources and data sets in real-time and generate a trustable DQScore™ with the ability to track, manage and improve data quality over time.
DQLabs Continuous DQ monitoring uses statistical and machine learning approaches to detect data outliers and anomalies.
Remediate Data Quality Issues by cleaning, enriching and merging good records using ML based Smart Curation and Self Learning
Measure business outcomes and receive valuable insights for recommendations using out of the box dashboards.
Using DQLabs smart connectors that comes out of the box, you can connect to an unlimited amount of data sources in any form, shape and any location.
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Readily available insights on alerts and data issues across your data stack powered with business dashboards and configurable widgets.
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Out-of-the-box advanced anomaly detection algorithm detects anomalies across all metadata and custom measures.
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