This article explains how to connect with, and use data from, SharePoint sites — using the file system via OneDrive — for operations in IRI Workbench-supported data management software.
Abstract: IRI has partnered with Windocks to provide an on-demand, test-ready virtualized repository that delivers masked, subsetted or synthesized databases in seconds for #docker containers, conventional instances or workstations.
This article is part of a series of IRI blog articles explaining how to use the IRI DarkShield data masking product for semi- and unstructured data sources.
Like previous articles in this blog on the connection and configuration of other relational databases with the IRI Voracity data management platform — and its ecosystem products: CoSort, NextForm, FieldShield, DarkShield and RowGen — this article details how to reach DB2 sources.
IRI DarkShield is a data masking tool for finding and de-identifying Personally Identifiable Information (PII) and other sensitive data in semi-structured and unstructured files and databases.
Whether your SQL Server database is on-premise or in a cloud platform like Azure, its data is accessible for movement and manipulation in IRI Workbench-supported products like CoSort, FieldShield, DarkShield, NextForm and RowGen, or the IRI Voracity platform which includes them all.
Usually static data masking is performed on production data at rest so it is stored safely, or when replicated to non-production environments for testing or development purposes.
IRI Workbench provides a number of features for working across multiple tables in a database. It includes wizards to: profile databases; classify columns; subset, mask and migrate data; generate test data; etc.
An operational data store (or “ODS”) is another paradigm for integrating enterprise data that is relatively simpler than a data warehouse (DW).
Quasi-identifiers, or indirect identifiers, are personal attributes that are true about, but not necessarily unique, to an individual. Examples are one’s age or date of birth, race, salary, educational attainment, occupation, marital status and zip code.
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 HIPAA Expert Determination Method security rule.