Hanzo & Nightfall AI To Present Educational Webinar Driving Data Intelligence Using Collaboration Content

Hanzo Logo

Extract from Sarena Regazzoni’s article “Hanzo & Nightfall AI To Present Educational Webinar Driving Data Intelligence Using Collaboration Content”

Hanzo, a technology pioneer in preserving, collecting, reviewing, and exporting dynamic, complex collaboration and web-based data, in partnership with Nightfall AI, the first cloud-native extensible data loss prevention (DLP) platform, announce an upcoming educational webinar held at 1:00 pm EDT on Tuesday, May 24. The webinar, Drive Data Intelligence with Collaborative Data will explore how enterprises can improve their information governance processes to support effective and efficient investigations and ediscovery by leveraging the power of data loss protection detection engines on ediscovery data to highlight issues and topics of interest.

Event Description

Data volumes are growing at breakneck speeds and managing risk with collaborative enterprise data sources becomes more critical as the work from home trend persists. Enterprise legal, compliance, and governance teams struggle to detect, manage, govern, and protect the information in near real-time. Similarly, litigation, HR, and investigation teams struggle with data intelligence on information they have collected from cloud applications like Slack and Google Workspace. 

In this webinar, industry leaders will discuss the challenges enterprises face with collaborative data, and how enterprises can broaden their horizons and gain insights into their data using powerful ML-enriched data.  Teams can discover more to quickly find sensitive data such as PII, secrets, and undesirable language that might otherwise go undetected within collaboration content. We’ll also share some compelling real-world examples of how companies can leverage Data Loss Prevention (DLP) and ML-enriched data to make their governance, discovery, and compliance processes safer, more informed, and more efficient.  

Read more here

ACEDS