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Database Performance and Protection
There are a number of performance problems inherent in very large database (VLDB) environments, including:
- Searching, profiling and classifying data
- Change data capture
- Query response
- Extraction
- Reorgs
- Bulk loads
- Data (PII) masking
- Migration and replication
- Large scale testing
Before you resort to:
- A newer DB version or server
- A DB or ELT appliance
- SSD or Hadoop
- In-memory databases
- DB-specific column encryption
- A megavendor masking or TDM product
try IRI's less invasive, less expensive, less complicated, and more proven approaches available within the IRI Voracity data management platform or in the individually available software below:
Process
Use IRI Voracity or IRI NextForm DB Edition to discover, map, replicate, and load data in new target tables, while also being able to transform, cleanse, mask, and report at the same time.
Use the Offline Reorg wizard in IRI Workbench, which combines FACT, CoSort, and your DB's bulk load utility.
Filter, sort, join, aggregate, reformat and otherwise transform and target table in multiple sources and formats in IRI Voracity ETL workflow and transform mapping diagrams.
Propel
Use IRI FACT (Fast Extract) to parallel-unload tables to flat files via native drivers for Oracle, DB2, Sybase, SQL Server, MySQL, Altibase, Greenplum and Teradata.
Reorder large tables in query order with IRI CoSort or the multi-table Offline Reorg wizard in the IRI Workbench GUI for Voracity, built on Eclipse™.
Sort on the primary index key with CoSort or Voracity, pipe the results to SQL*Loader, DB2 Load, bcp, etc., and rebuilt the index later.
Protect
Any product you license from IRI includes the free IRI Workbench GUI for all IRI products, built on Eclipse, which features multiple tools for data discovery in any JDBC-connected source.
Encrypt PANs and de-ID sensitive data in DB columns with data masking functions in Voracity or FieldShield.
Statistically measure the risk of re-identification from demographic and other quasi-identifying student or patient information using built-in risk scoring technology in IRI FieldShield and then use its data blurring and bucketing functions to anonymize that data.
Prototype
Learn from our Total Data Management primer to plan for the creation and distribution of policy-driven, realistic test data sets.
Use IRI RowGen or Voracity to automatically parse DDL, generate (and modify) the test data, and populate with pre-configured loader scripts.
Use the DB subsetting wizard in the IRI Workbench GUI for Voracity.
