Data Consolidation Wizard for Data Quality
Given the amount of data businesses garner daily from human interaction, it is easy to understand how their sources become rife with redundant or erroneous entries. Read More
Single Job Execution Options in IRI Workbench
IRI Workbench not only has several ways to create jobs, but also several ways to execute them.
This article focuses on IRI Workbench execution options for job scripts based on the SortCL program language, which covers IRI Voracity ETL, CDC, SDC, pivoting and subsetting jobs, as well as its constituent product functions; i.e., Read More
The Use of Data Lakes
Has your organization considered using a data lake? This article explains what a data lake is, and posits a data lake architecture optimized for analytic results. Read More
The Importance of a Unified View of the Customer
Customers drive business, and they want to be understood and valued. That starts with getting their (only) name right, and having an accurate view of their transaction history, preferences, and related information. Read More
Data Quality and Fuzzy Searching
IRI is now also delivering fuzzy search functions, both in its free database and flat-file profiling tools, and as available field-function libraries in IRI CoSort, FieldShield, and Voracity to augment data quality, security, and MDM capabilities. Read More
Creating E-R Diagrams in IRI Workbench
The Entity-Relationship Diagram (ERD), or entity relationship model, is a visual depiction of database tables (entities) and how they are linked through primary and foreign keys (relationships) to each other. Read More
Drawing Values from Set Files
This article looks at sets from an informational processing perspective; what they are; how they are constructed; and, distinct ways in which data can be drawn from sets within IRI software products using the SortCL data definition and processing program; i.e., Read More
Data Quality – Catching Rule Violations
Introduction This is my third installment of blog articles about Data Quality. In the first article, I postulated that data has quality when it has an acceptable level of errors. Read More
Database Profiling in IRI Workbench
Editors Updates: Q2’16: In addition to the database profiling wizard in the data discovery menu group in IRI Workbench described below, IRI has introduced robust data classification that enables the application of field rules for multi-source data transformation and protection through data class libraries. Read More
Connecting to 84 More Data Sources
Data architects and data scientists, as well as DBAs and governance teams, may need to use or migrate data in legacy file formats and databases. Additionally, the ability to mash-up those sources with newer file and database repositories is important in data integration (ETL) and analytic projects, as well as in data profiling for data loss prevention and privacy law compliance. Read More
Using Data Templates to Find Data Format Errors
In Working towards Data Quality, we defined data quality (DQ) as a state in which data can be used for operations. What makes the quality of data high is the paucity of errors. Read More