"Databricks reminds us of the danger of data fragmentation, which has only become more acute with the rise of AI agents. The existence of data silos means that AI has to deal with fragmented data, which causes delays and security problems. The company sums up the fragmentation problem as follows: "slower responses, limited visibility, and more risk in general." Databricks repeatedly refers to a "unified" system when it comes to Data Intelligence for Cybersecurity."
"Together with partner security parties, Data Intelligence for Cybersecurity should come into its own. Early customers such as Arctic Wolf, Barracuda Networks, and Palo Alto Networks are already talking about the major benefits of adopting Databricks' new offering. For example, Databricks enables Barracuda to achieve a 75 percent reduction in processing and storage costs, in addition to real-time alerting within 5 minutes. Thanks to Databricks, Palo Alto has been able to triple the speed of its own threat detection features."
Databricks aims to unify security data to address fragmentation that slows responses, reduces visibility, and increases risk. The platform consolidates data in a lakehouse and supports building AI agents with Agent Bricks. The lakehouse provides centralized attack-surface visibility without SIEM vendor lock-in. The offering is designed to work with partner security vendors rather than to replace them. Early customers report large operational gains: Barracuda cites a 75% reduction in processing and storage costs and five-minute real-time alerting; Palo Alto reports triple the speed of threat detection. Arctic Wolf processes over 8 trillion events weekly using the platform.
Read at Techzine Global
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