This is a business intelligence software and data integration tool to access and mash up multiple data sources in real time. It virtualizes data to be accessed by any off-the-shelf BI tool with ODBC/JDBC connectivity.

dataWerks provides data integration software that delivers genuine user empowerment by giving business users the ability to access and mashup multiple data sources in real time. dataWerks virtualizes your data so that it can be accessed by your preferred off-the-shelf BI tool using ODBC/JDBC connectivity. No retraining of users is necessary because they can continue to use familiar BI applications. Bottom line: deploying dataWerks enables business users to ‘plug and play’ with massive data sets and with minimal disruption to existing processes. Big data integration is possible today!

The unified data layer is virtual. Unlike Extract Transform Load (ETL) processes, the majority of the data remains in place, and is queried on-demand directly from the source systems. This reduces mass data movement and brings the end user closer to the original data sources – minimizing the challenges and costs of multi-level data movement and transformation. Data Virtualization is faster and more flexible than traditional Data Integration (DI) – no mass data replication, no new data architecture, no mass data storage.

The unified data layer serves as an abstraction layer for creating data mashups across sources and formats. It reads and analyzes data from multiple sources including structured, unstructured, web, and big data; and makes the data available for integrated querying, reporting, and analytics. Data consumers don’t need a deep understanding of the complex structures and different formats of the underlying data sources. The mashed-up data is accessible through different interfaces including SQL, web services, data dumps/CSV, and pre-formatted reports.

Key Features

  • Data virtualization
  • Data integration
  • Data mashup
  • No data replication
  • Timely insights across disparate data sources
  • Hiding of complexity of underlying data structures
  • Multi-channel and multi-mode data access
  • Immediate results and incremental improvements
  • No data lakes
  • Getting results in under one second



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