
Sign up to save your podcasts
Or
Centralize, retain, and query high-volume, long-term security data across Microsoft and third-party sources for up to 12 years using Microsoft Sentinel’s new unified data lake. Correlate signals, run advanced analytics, and perform forensic investigations from a single copy of data—without costly migrations or data silos. Detect persistent, low-and-slow attacks with greater visibility, automate responses using scheduled jobs, and generate predictive insights by combining Copilot, KQL, and machine learning.
Vandana Mahtani, Microsoft Sentinel Principal Product Manager shows how to uncover long-running threats, streamline investigations, and automate defenses—all within a unified, AI-powered SIEM experience.
► QUICK LINKS:
00:00 - Microsoft Sentinel Data Lake
01:49 - Data Management
02:46 - Table Management
03:36 - Data Lake exploration
04:17 - Advanced Hunting
05:23 - Query retention data
06:16 - Automate threat detection
07:18 - Move from reactive to predictive
08:50 - Wrap up
► Link References
Check out https://aka.ms/SentinelDataLake
► Unfamiliar with Microsoft Mechanics?
As Microsoft's official video series for IT, you can watch and share valuable content and demos of current and upcoming tech from the people who build it at Microsoft.
• Subscribe to our YouTube: https://www.youtube.com/c/MicrosoftMechanicsSeries
• Talk with other IT Pros, join us on the Microsoft Tech Community: https://techcommunity.microsoft.com/t5/microsoft-mechanics-blog/bg-p/MicrosoftMechanicsBlog
• Watch or listen from anywhere, subscribe to our podcast: https://microsoftmechanics.libsyn.com/podcast
► Keep getting this insider knowledge, join us on social:
• Follow us on Twitter: https://twitter.com/MSFTMechanics
• Share knowledge on LinkedIn: https://www.linkedin.com/company/microsoft-mechanics/
• Enjoy us on Instagram: https://www.instagram.com/msftmechanics/
• Loosen up with us on TikTok: https://www.tiktok.com/@msftmechanics
4.2
2020 ratings
Centralize, retain, and query high-volume, long-term security data across Microsoft and third-party sources for up to 12 years using Microsoft Sentinel’s new unified data lake. Correlate signals, run advanced analytics, and perform forensic investigations from a single copy of data—without costly migrations or data silos. Detect persistent, low-and-slow attacks with greater visibility, automate responses using scheduled jobs, and generate predictive insights by combining Copilot, KQL, and machine learning.
Vandana Mahtani, Microsoft Sentinel Principal Product Manager shows how to uncover long-running threats, streamline investigations, and automate defenses—all within a unified, AI-powered SIEM experience.
► QUICK LINKS:
00:00 - Microsoft Sentinel Data Lake
01:49 - Data Management
02:46 - Table Management
03:36 - Data Lake exploration
04:17 - Advanced Hunting
05:23 - Query retention data
06:16 - Automate threat detection
07:18 - Move from reactive to predictive
08:50 - Wrap up
► Link References
Check out https://aka.ms/SentinelDataLake
► Unfamiliar with Microsoft Mechanics?
As Microsoft's official video series for IT, you can watch and share valuable content and demos of current and upcoming tech from the people who build it at Microsoft.
• Subscribe to our YouTube: https://www.youtube.com/c/MicrosoftMechanicsSeries
• Talk with other IT Pros, join us on the Microsoft Tech Community: https://techcommunity.microsoft.com/t5/microsoft-mechanics-blog/bg-p/MicrosoftMechanicsBlog
• Watch or listen from anywhere, subscribe to our podcast: https://microsoftmechanics.libsyn.com/podcast
► Keep getting this insider knowledge, join us on social:
• Follow us on Twitter: https://twitter.com/MSFTMechanics
• Share knowledge on LinkedIn: https://www.linkedin.com/company/microsoft-mechanics/
• Enjoy us on Instagram: https://www.instagram.com/msftmechanics/
• Loosen up with us on TikTok: https://www.tiktok.com/@msftmechanics
3,016 Listeners
1,982 Listeners
867 Listeners
364 Listeners
381 Listeners
640 Listeners
736 Listeners
370 Listeners
1,395 Listeners
1,017 Listeners
62 Listeners
188 Listeners
57 Listeners
127 Listeners
505 Listeners