Real Time Threat Detection
Since 2013, cybercriminals have stolen over 14.7B digital records from organizations across the industry. Responding quickly to threats is critical to avoiding a breach. To do this successfully, the private sector and government organizations need to monitor and analyze billions of data signals in real-time and perform ad-hoc analysis over large time windows of historical data. Yet, existing security tools are struggling to keep up. Overcoming these challenges requires a new approach to threat detection rooted in big data, analytics and AI. Join this technical deep-dive to learn about the latest trends in data-driven cybersecurity and hear how one of the world’s largest tech companies is using Databricks, the cloud and open-source big data technologies like Apache Spark™ and Delta Lake to scale threat detection and prevent attacks in real-time. In this Deep dive you will learn: About the current state of cybersecurity How real-time data analytics and AI can help the private sector and government agencies uncover anomalous behavior patterns and protect against threats. How one of the world’s largest tech companies uses Apache Spark, Delta Lake, and other open-source tools to enable threat detection at petabyte-scale Live demo on how to build real-time threat detection pipelines using machine learning
Session ID: Presentation Type: On-Demand Session (Recorded)
Date / Time: [Content On-Demand] @ On Demand ET (US)
Presented by:Databricks is the data and AI company. Thousands of organizations worldwide rely on Databricks’ open and unified platform for data engineering, machine learning and analytics. Founded by the original creators of Apache Spark™, Delta Lake and MLflow, Databricks is on a mission to solve the world’s toughest problems. Click for more details and additional sessions and content.
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