Browsing the Operational Data Store (ODS)
What Is an ODS?An operational data store (or “ODS”) is another paradigm for integrating enterprise data that is relatively simpler than a data warehouse (DW). Read More
An operational data store (or “ODS”) is another paradigm for integrating enterprise data that is relatively simpler than a data warehouse (DW). Read More
In the last couple of years since this article about the use of IRI CoSort as a parallel data manipulation alternative to Hadoop, IRI released the Voracity platform to process big data in either paradigm. Read More
Many of the same data manipulation, masking, and test data generation jobs you can run in IRI Voracity® with the default SortCL program can now also run seamlessly in Hadoop™. Read More
Enterprise data continues to change rapidly in form, size, use, and residence. Rarely does it remain in siloed constructs anymore, limited to certain business units or untouched by the outside world. Read More
Talend has been on the market for a few years now, and its flexible UI components make it a very reasonable choice for developers when it comes to customization. Read More
Has your organization considered using a data lake? This article explains what a data lake is, and how you can fish its murky depths for value in an architecture optimized for your needs. Read More
IRI has completed its first Software Development Kit (SDK) for RowGen that Java programmers can call to generate test data dynamically in applications or across Hadoop nodes. Read More
Among analytic tools for statistical computation and graphics, R has shown an increase in popularity among data miners, and in the development of its open source language. Read More
As the old English proverb says, “necessity is the mother of invention.” When it comes to modern business intelligence goals, these words of wisdom ring truer than ever. Read More
Before Big Data became a buzz word and Gartner hype cycle fodder (never mind falling into the ‘Trough of Disillusionment‘), companies like IRI were handling it. Read More