Augmented Data Integration

Effectively combine all your data from a variety of sources to get a single view of your organization’s data using our AI powered built-in connectors.

Data Integration

In today’s world, organizations need faster access to integrated data across an increasingly distributed landscape with data spread across the cloud, on-premise and within legacy systems. Extreme levels of diversity, distribution and scale are adding tremendous complexity to the efforts of overall data integration. The traditional architectures and tools for data integration focused on replicating and moving data. They were slow and inexact in delivering semantically enriched and integrated datasets.

However, with DQLabs’ augmented data integration platform you now have the ability to use AI/ML algorithms to deliver “just-in-time” data management. Implementing infrastructure and processing maps for data integration use cases, both business and technical users can solve their requirements for hybrid/multi-cloud data management including augmented data integration and data fabric designs.

Augmented Data Integration Features

Leverage DQLabs augmented data integration featuring the user-friendly ready-made plug and play platform, applicable for any data source type and any data location with support for governance and enterprise-wide management of data assets.

Combine different data destinations

Supports easy access to and delivery from various data silos by implementing well-understood, established integration technologies utilizing best practices and standards. More importantly it’s flexible enough to support integrated data through a combination of data delivery styles.

Active metadata analysis

AI/ML-augmented data integration enables active metadata analysis, semantics and a knowledge graph by offering an augmented data catalog which provides an inventory of all types of metadata assets and their relationships.

Versatile Data Access

DQLabs provides multiple levels of access at the attribute, dataset, and data source level to provide for ease of data access and permissioning.

Process at speed

DQLabs provides massive parallel processing capabilities to deliver distributed processing to rationalize the performance of data integration workstreams, distributable integration flows (via push-down processing) and easy-to-deploy optimization capabilities.

API support

Provision data dynamically using APIs in synergy with data and application integration techniques including access, lookups and also delivery of data through a centralized permissioning layer.

Data Integration

The extreme levels of diversity, distribution, scale, and complexity in an organizations’ data assets are adding tremendous complexity to the overall data integration and data management tasks. DQLabs combines different data integration styles and by using proven integration technologies, best practices, and standards, delivers scalable out of the box connectors with a unified data integration strategy.

  • DQLabs continuously finds and integrates catalogs, sharing all forms of metadata
  • Save time and money with the ability to deliver a just-in-time data management infrastructure
  • Simplify your DQ process as DQLabs extracts and centralizes data across multi-cloud, hybrid cloud, on-premises, and third-party applications
  • Benefit with the use of metadata analysis, semantic identification, and knowledge graphs as part of the data ingestion process
  • Easily and effectively scale and distribute your DQ process based on your workload in real-time

Best Practices

See what DQLabs can do

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