BigID Data Isights
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BigID Data Isights
|Company (that provides the nominated product / solution / service)||BigID|
|Company size (employees)||10 to 49|
|Type of solution||Software|
In 3 bullets, summarize why this product or service is different from the competition and deserves recognition:
- identity data intelligence to provide unique vantage and POV appropriate for privacy regulations
- no data copying or centralization
- ability to easily enrich data with business context and external data (access logs, consent logs, outside data)
Summary of Achievements
BigID identity data intelligence platform helps organizations find, map and govern identity-centric data across a distributed enterprise estate. The BigID solution has a unique ability to identify identity data content and also context like access, risk, purpose-of-use to give organizations a complete bottom-up view of their data from an identity perspective.
The identity-centricity allows BigID to go beyond traditional classification/cataloging products to provide a broader protection, privacy, and compliance capability than available from traditional tools. Identity is essential firstly for understanding and satisfying emerging regulations like GDPR which are centered on people information. BigID uniquely has an ability to find a broader array of data, across the data center and cloud, in any language without clunky surveys or RegX.
Using BigID organizations can fully catalog their data, identify duplicates or quality issues, simplify matching for enrichment, resolve entities, track access and show provenance/lineage and even virtualize access. Moreover, it can do this while providing identity context (person, client, SKU, IP, ..) and without building a complex or expensive data warehouse.
Like Google, BigID provides a way to navigate and govern data without creating a data lake or warehouse. BigID only maintains pointers to the data so that organizations can get a central view without centralizing the data. Moreover, BigID allows organizations to supplement found data with survey data for collection of business context (like purpose-of-use) and also cross-correlated data from other sources (like consent logs).