IRI Blog Articles

Diving Deeper into Data Management



ūüé• One Big Data Integration Engine, Three Business Intelligence Paths

by Lisa Mangino

As IRI CoSort integrates and stages big data from a variety of sources, it plays a natural role in producing data for reporting and analytics.

CoSort not only transforms data for loading data warehouse tables, it can report at the same time, or feed data in filtered, aggregated, sorted, and properly formatted subsets (like .CSV files) that BI tools can handle.  Check out this overview video or continue reading below:

With CoSort, you can go in any of the directions below that makes the most sense to you:

1) Embedded BI. Use the built-in 2D reporting functions in the CoSort Sort Control Language (SortCL) program. Design custom detail, delta, and summary reports in scripts you write or build graphically in the IRI Workbench IDE, built on Eclipse.

For more information on the report formatting capabilities of SortCL, see:

XBRL format support, fuzzy logic analysis, and sliding aggregate windows, and¬†PCI compliant data masking, are some of SortCL’s newer features for FSI reporting.

2) Fast Hand-offs to Major BI tools. CoSort’s SortCL program is most often used to prepare, or franchise, huge volumes of data for use in dashboards, BI tools, reporting programs, cubes, data or spread marts, and so on.


CoSort users routinely use SortCL to transform and feed data to Business Objects, Cognos, Dimensional Insight, Excel, iDashboards, Microstrategy, SQL reports, and others.

3) Direct Interplay with Eclipse BIRT. BIRT is a free, open source plug-in for the Eclipse graphical IDE, just as the IRI Workbench GUI is:

Eclipse co-location and ODA integration between CoSort and BIRT allows SortCL users to prepare and feed data seamlessly into BIRT displays, shifting the transformation burden to where it belongs Рon CoSort in the file system.

BIRT users can specify an IRI Data Source to ingest filtered, cleansed, sorted, aggregated, and masked data either before, or at the actual moment of, reporting.

For more information, see: and step-by-step instructions in this article or you can watch a video presentation on how we accelerate data processing for analytics here:

Print Friendly

{ 0 comments… add one now }

Leave a Comment

Previous post:

Next post: