Data Quality (DQ)
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
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
Big Data
“Progress is impossible without change, and those who cannot change their minds cannot change anything.”
-George Bernard Shaw
The mathematical symbol for change is the Greek uppercase letter delta: Δ. Read More
Data Quality (DQ)
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 Masking/Protection
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
Data Masking/Protection
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 (DQ)
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
IRI Workbench
Master Data Management (MDM) is a strategic enterprise information management (EIM) life cycle initiative designed to foster the consistency and accurate maintenance of master (or reference) data. Read More
Data Quality (DQ)
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
Data Quality (DQ)
Introduction
In this article, I suggest ways to move your company’s data towards a higher state of quality. The highest quality occurs when the data meets the needs of your company. Read More
