Structured Data
ETL, Migration, Masking, Reporting, Prototyping
For more than 45 years, IRI software has been manipulating 'big data.' IRI began using that term in 2004 to describe its customer's high volume input sources.
IRI software can address structured data in mainframe sequential and other flat-file formats database tables, and web logs, plus many other data sources through native connectors to streams like KAFKA or MQTT, cloud silos like Amazon S3 and Azure, NoSQL DBs like MongoDB and DynamoDB, and network protocols like HTTP/S and S/FTP.
The most relied-upon corporate and open data exists in these forms, and IRI software works with it in many ways through a simple metadata, supported in Eclipse:
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extracts very large database (VLDB) tables to flat files or pipes |
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sorts, joins, aggregates and otherwise transforms data in multiple sources, and creates multiple targets (including custom reports) at once |
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converts and replicates data types, file formats, and database table structures for platform and application migration, data federation, etc., and structures unstructured data |
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mask data in files and tables at the field level with encryption and many other protection functions |
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generates big test data in structurally and referentially correct RDB table, flat-file, and formatted-report targets |
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supports all of the above and discovers, integrates, migrates, governs, analyzes, and curates file and DB data throughout its lifecycle |
