Data Provisioning Style for Data Integration Tools

This is the last day of 2013, and probably the last blog for this year from me. In this blog I wish to discuss the various ways the Data Integration tool delivers the data for Enterprises.

Traditionally most data integration tool vendors offered bulk-batch data movement via extraction, transformation and loading (ETL) functions. But Enterprises increasingly expect to deploy data integration tools for a broad range of use cases like the following:

  • BI, Analytics and (Logical) Data Warehousing
  • Data Consistency Between Operational Applications
  • Data or System Migrations and Consolidations
  • Master Data Management
  • Inter-enterprise Data Acquisition or Sharing

This expectation is driving demand for comprehensive data delivery capabilities. The following are the 4 critical data delivery capability that Enterprises are expecting any Data Integration tool to support.

  • Bulk-batch data movement involves bulk and/or batch data extraction and delivery approaches (such as support for ETL processes) to consolidate data from primary databases and formats. This capability draws on data from across systems and organizational boundaries.
  • Data federation/virtualization executes queries against multiple data sources to create virtual integrated views of data in memory (rather than physically moving the data). Federated views require adapters to various data sources, an active metadata repository and a distributed query engine that can provide results in various ways (for example, as an SQL row set, XML or a Web services interface).
  • Message-oriented movement encapsulates data in messages that various applications can read so that they can exchange data in real time. I have covered some aspects of this in a previous blog.
  • Data replication and synchronization synchronizes data, such as enabling change data capture (CDC), between two or more database management systems (DBMSs), schemas and other data structures, whether of the same type or different types. This capability supports high-volume and mission-critical scenarios in keeping operational data current in multiple systems.

So where does IBM Stand amongst the various data integration tool vendors in this critical tool capability?


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