expressor fills a major gap in QlikTech's emerging enterprise architecture. (See my previous blog titled "QlikView Goes Enterprise".) The new functionality will make it easy for QlikView developers to build and manage data workflows across multiple QlikView applications and maintain consistent definitions of commonly used metrics and data elements.

Currently, QlikView developers must manually manage metadata definitions using QlikView script, which can be cumbersome, time consuming, and prone to error. Adding expressor to the QlikView architecture will automate the process of building and deploying QlikView applications throughout an enterprise.

expressor Functionality

As a data integration company, expressor came relatively late to the market, launching its flagship product in 2008. Since then, the company has maintained a relatively low profile, selling through partners and to small-and-medium sized businesses with a small direct salesforce. Yet, the tool is a fully-featured and highly parallelized data integration engine whose key differentiation is its semantic framework that fosters reuse and standardization within and across data integration projects. Sometimes, late to market is better.

With expressor Studio, developers can create data flow objects that define commonly used metrics and data elements throughout the organization. The expressor engine then automatically maps sources and targets to the predefined objects, saving developers an enormous amount of time. This approach also simplifies data flows and preserves information consistency across projects.

Enterprise Deployments

expressor will help ingratiate QlikView with IT and data warehousing professionals who often view QlikView as a data shadow system that undermines enterprise semantics. QlikView customers can use expressor to build data flows for new applications or rewire existing QlikView applications to pull data from expressor rather than source systems. expressor enables developers to ensure that all QlikView applications apply consistent definitions to shared metrics and data elements.

In some respects, the acquisition catapults QlikTech past many enterprise BI players in the market that don't embed a data integration tool and rely on data warehouses or data marts to preserve enterprise semantics. The addition of expressor will enable QlikView to integrate more seamlessly with existing semantic repositories as well as create its own where no data warehouse or data mart exists.

To foster integration with existing data warehousing environments, QlikTech should consider developing migration tools that convert data flows from leading data integration vendors, such as Informatica, into expressor data flows. One expressor partner, Bitwise, has already done this. QlikTech should also consider investing in a data quality and cleansing tool to round out its newly acquired data integration capabilities.