AI-Powered EDR: Streamlining Blackberry Cybersecurity with Databricks
OVERVIEW
EXPERIENCE | In Person |
---|---|
TYPE | Breakout |
TRACK | Data Governance |
INDUSTRY | Enterprise Technology |
TECHNOLOGIES | Delta Lake, GenAI/LLMs, Governance |
SKILL LEVEL | Intermediate |
DURATION | 40 min |
DOWNLOAD SESSION SLIDES |
Cybersecurity incidents are costly, and using an endpoint detection and response (EDR) solution enables the detection of cybersecurity incidents as quickly as possible. To effectively detect cybersecurity incidences requires the collection of millions of data points and the storing and querying of endpoints data presents considerable engineering challenges without creating internal data silos. Databricks tooling enabled us to break down our data silos and iteratively improve our EDR pipeline to ingest data faster and reduce querying latency by more than 20% while reducing costs by more than 30%. In this session, we will share the journey, lessons learned, and the future for collecting, storing, governing, and sharing data from endpoints in Databricks. The result of building EDR using Databricks helped us accelerate the deployment of our data platform and power our cybersecurity co-pilot.
SESSION SPEAKERS
Justin Lai
/Distinguished Data Architect
BlackBerry
Robert Lombardi
/Director Product Management
Blackberry
Digan Parikh
/Sr. Solutions Architect
Databricks