DataBahn and Microsoft accelerate SIEM deployment through integration
Briefly

DataBahn and Microsoft accelerate SIEM deployment through integration
"DataBahn's AI-driven connectors automatically normalize, enrich, and route telemetry from more than 500 sources to Microsoft Sentinel. DataBahn's Cruz AI engine determines which data to send to the analytics tier and which to the Sentinel data lake for long-term storage. Customers report cost savings of up to 60 percent on Sentinel ingestion thanks to this intelligent tiering mechanism."
"Organizations that deploy Microsoft Sentinel as their SIEM platform often encounter slow onboarding of log information sources, manual normalization, and increasing ingestion costs as the amount of telemetry grows. This can take weeks or even months. DataBahn positions itself as a data fabric in front of Sentinel, resolving complexity outside the SIEM platform."
"The solution is available through Microsoft Marketplace, enabling organizations to leverage their existing Microsoft Azure Consumption Commitments (MACC) for DataBahn. This simplifies procurement and shortens purchasing cycles."
DataBahn and Microsoft are expanding their partnership to integrate deep AI capabilities into Microsoft Sentinel, addressing critical SIEM deployment challenges. Organizations using Sentinel typically face slow onboarding of log sources, manual normalization requirements, and escalating ingestion costs. DataBahn functions as a data fabric positioned before Sentinel, automatically normalizing, enriching, and routing telemetry from over 500 sources. The Cruz AI engine intelligently determines which data routes to the analytics tier versus the Sentinel data lake for long-term storage. This intelligent tiering mechanism delivers cost savings up to 60 percent on Sentinel ingestion. The solution is available through Microsoft Marketplace, allowing organizations to apply existing Microsoft Azure Consumption Commitments for simplified procurement and faster purchasing cycles.
Read at Techzine Global
Unable to calculate read time
[
|
]