Data Transformation
Forty years after the first release of IRI CoSort for CP/M, CoSort v10 for Unix, Linux, and Windows platforms was released in the middle of 2018. Read More
Data Masking/Protection
IRI has discussed startpoint security in further detail with the Outlook Series in a segment about data masking.
This article defines what we’d like to call “startpoint security” mostly by virtue of a comparison to endpoint security. Read More
Big Data
According to Simson L. Garfinkel at the NIST Information Access Division’s Information Technology Laboratory,
De-identification is not a single technique, but a collection of approaches, algorithms, and tools that can be applied to different kinds of data with differing levels of effectiveness. Read More
IRI Workbench
As we transition IRI Workbench to the Neon version of Eclipse™ in 2017, the Easy Shell feature that facilitated command-line executions of job and batch scripts will no longer be available. Read More
Big Data
To analyze data successfully, it must first be prepared successfully. Poor quality data creates poor results. Worse yet is data that takes too long to collect and clean because it is too big or too foreign. Read More
Data Transformation
For the last 30 or so years, the precursor to most large scale business intelligence (BI) environments has been the Enterprise Data Warehouse (EDW). A data warehouse (DW) is usually a central database (DB) for reporting, planning, and analyzing summarized, subject-matter data integrated from disparate, historical transaction sources. Read More
IRI Business
The other day, two different companies selling me services asked if their offering were in my wheelhouse. Since I didn’t know I had a wheelhouse, I couldn’t answer them.I Read More
Big Data
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
Test Data
This article is the last of a 4-step series introduced here.
Step 4: Test Data Sharing & Persistence
Being able to modify, deploy, store, and re-use test data is important. Read More
Data Quality (DQ)
This article is part of a 4-step series introduced here. Navigation between articles is below.
Step 3: Test Data Generation & ProvisioningIn prior steps outlined in this series, you have determined the purpose and properties of the data, and who will produce and consume it. Read More