This article is the fourth in our 4-part series on feeding the Datadog cloud analytic platform with different kinds of data from IRI Voracity operations. It focuses on visualizing search logs from the DarkShield unstructured data masking product (also a Voracity component) in Datadog for security analytics.
This article is the second in a 4-part series on feeding the Datadog cloud analytic platform with different kinds of data from IRI Voracity operations. It focuses on preparing data in Voracity, and getting Datadog ready to receive it.
Elasticsearch is a Java-based search engine that has an HTTP interface and stores its data in schema-free JSON documents. Unfortunately, a spate of costly and painful breaches of Personally Identifiable Information (PII) continue to plague online Elasticsearch databases:
Were all the PII or other sensitive information in these DBs masked however, successful hacks and development copies may not be problematic.
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.
Just as IRI FieldShield product users can reach and mask personally identifiable information (PII) — and IRI Voracity platform users can integrate and govern structured files — in Amazon Simple Storage Service (Amazon S3) buckets, IRI DarkShield users can now find and mask PII in unstructured files stored in S3.