SIEMs remain the workhorse for many enterprise SOCs, but they are not without challenges. Rising costs, the ability to detect high-risk threats, and aging architecture that combines security analytics, logging, and data storage all in one monolithic and often vendor-specific stack, are contributing to enterprises seeking ways of using their data in more effective ways.
One area of particular interest is the adoption of modern, cost-effective security data lakes that have shown utility in advanced data science use cases.
However, it’s not always clear how enterprise organizations can take advantage of these new security data lakes, what the first steps are to get started, and what assurances there are that you will be able to adopt security data lakes alongside your existing SIEM without the need to rip and replace.
DISCUSSION POINTS
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Join John Banghart for a moderated discussion that will feature insight from Mackenzie Kyle, VP of Product event sponsor Anvilogic, and will also draw upon the experiences of the attendees. Participants will explore strategies for data lake migration, reskilling teams, and managing migration risk.
This session will be:
VP of Product
Anvilogic
Prior to Anvilogic, Kyle led the Cybersecurity Operations Center team at one of the largest financial institutions in the U.S. He has over a decade of experience in cybersecurity and threat detection.
950 I St NW Washington, DC 20001
Anvilogic is a Palo Alto-based AI cybersecurity startup founded by security veterans and data scientists from Fortune 500 companies. Our mission is to democratize threat detection and hunting for today’s SOC teams to easily be done across hybrid, multi-clouds and security data lakes without needing to centralize data or rip and replace tools. Further, with our investments in AI-powered automation of detection-as-code to create, test, tune and deploy detections, SOC users can implement high-efficacy detection and hunting techniques without writing a single line of code nor manually wrangling data.
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