Data Integration

Streamlines and tracks data integrated from varied sources.

Data integration is a core part of any information-driven business. Yet, integrating data is often a slow, labor-intensive, and error-prone process that yields incomplete or inflexible results. Anzo transforms this practice through the use of business user friendly conceptual or logical models that greatly simplify the integration of any data from any source. These reusable canonical models form a virtual hub in a hub-and-spoke ETL/ELT architecture used to integrate data through automatically created Apache Spark™ data movement and transformation jobs in a fraction of the time it would take otherwise. The same conceptual models can be used to track information brought into the data repository from spreadsheets and unstructured data sources.

  • Key Benefits
  • Use Cases
  • Capabilities
  • Integrate data in hours or days rather than weeks or months
  • Combine enterprise data with data from outside your firewall
  • See the big picture by combining conventional database data with data from spreadsheets and unstructured text
  • Iteratively change, extend and adapt integrations without starting from scratch
  • Enable business analysts to integrate new sources of data without relying on IT
  • A large financial services provider uses Anzo to automate the integration of customer data with internal data to bring customers on-board five times faster than before Anzo.
  • A pharmaceutical company uses Anzo to integrate structured and unstructured competitive intelligence data that previously needed to be manually curated.
  • Integrate structured, unstructured and semi-structured data
  • Automate the creation of traditional ETL jobs
  • Leverage industry standard models to drive integration
  • User-friendly self-service integration tools for business analysts