SCD Type 1
Dimensional data that change slowly or unpredictably is captured in slowly changing dimensions (SCD) analyses. In a data warehouse environment, a dimension table has a primary key that uniquely...
View ArticleSCD Type 2
Dimensional data that change slowly or unpredictably is captured in slowly changing dimensions (SCD) analyses. In a data warehouse environment, a dimension table has a primary key that uniquely...
View ArticleSCD Type 3
Dimensional data that change slowly or unpredictably is captured in slowly changing dimensions (SCD) analyses. In a data warehouse environment, a dimension table has a primary key that uniquely...
View ArticleSCD Type 6
Dimensional data that change slowly or unpredictably is captured in slowly changing dimensions (SCD) analyses. In a data warehouse environment, a dimension table has a primary key that uniquely...
View ArticleSCD Type 4
Dimensional data that change slowly or unpredictably is captured in slowly changing dimensions (SCD) analyses. In a data warehouse environment, a dimension table has a primary key that uniquely...
View ArticleIntroduction to Slowly Changing Dimensions (SCD)
A dimension is a structure that categorizes facts and measures similar to a categorical variable in statistics. The primary function of dimensions is to provide filtering, grouping, and labeling...
View ArticleThe 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...
View ArticleMDM Data Unification Wizard
Given the amount of daily data businesses garner from human interaction, it is easy to understand how their sources become rife with redundant or erroneous entries. For the sake of data quality and...
View ArticleThe Orca and IRI Voracity
Intelligent. Fierce. Powerful. Fast. Voracious. Killer whales, or orcas thrive in every world ocean and in many seas. They are intelligent, lively, and highly social creatures that form close,...
View ArticleFlat-File Profiling
Data profiling is the essential discovery process that helps you analyze, classify, cleanse, integrate, mask, and report on data in your repositories. With the information profile processes produce,...
View ArticleDirect Data Masking for MongoDB
In previous articles, we demonstrated file-based examples of masking data in, and generating test data for, MongoDB. Thanks to IRI’s recent partnership with Progress Software, you can now use...
View ArticleETL Task Tasking — Voracity Preview Features
During the design of IRI Voracity workflows in the IRI Workbench (Eclipse) GUI, you can preview the results of one or more transforms before saving or running the project. The preview can contain a...
View ArticleUnmasking the HL7 Data Standard
In this series of articles, we will describe the semi-structured HL7 file format used in many healthcare industry data storage and processing settings, and show how you can rapidly transform and mask...
View ArticleProcess and Protect HL7 Data with Voracity
This article shows how you can use IRI Voracity to rapidly integrate and mask sensitive healthcare data in the HL7 file standard we introduced here. Read More The post Process and Protect HL7 Data...
View ArticleHow to Build Realistic but Fake PII
There are times when it is necessary to test with or share data that has elements of personally identifiable information (PII). To comply with data privacy laws and prevent a data breach, you may need...
View ArticleDetecting Incremental Database Changes (Oracle to MongoDB ETL)
Detecting additions and updates to database tables for data replication, ETL, and other incremental data movement goals can be automated in IRI Voracity workflows designed and run in IRI Workbench...
View ArticleProduction Analytic Platform #1/4: Process on Par with Information
This is the first of a four-part series of blog articles examining the inherent tradeoffs between data processing and information storage and presentation within traditional ETL paradigms — from the...
View ArticleProduction Analytic Platform #3/4: Processing Real World Data
This is part 3 of a 4-part series on Production Analytics. Processing on Par with Information [Part 1] Data Processing Drives Efficiency [Part 2] Unifying the Worlds of Information and Processing...
View ArticleProduction Analytic Platform #4/4: Unifying the Worlds of Information and...
This is part 4 of a 4-part series on Production Analytics. Processing on Par with Information [Part 1] Data Processing Drives Efficiency [Part 2] Processing Real World Data [Part 3] In this final...
View ArticlePII (Age/Date) Blurring in IRI FieldShield
Adding ‘random noise’ to data through blurring or perturbation is a data common anonymization requirement for researchers and marketers of protected health information (PHI) seeking to comply with the...
View Article
