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- AI and cloud architecture are significant for managing security and deploying data, as increasing decentralized data necessitates centralized management and security.
- Druva Inc leverages AI and cloud architecture for data protection, aiming to provide enhanced cybersecurity resilience beyond simply utilizing more tools and focusing on network and vulnerability management.
- Dru AI automates manual tasks, analyzing logs to provide recommendations and high-fidelity data for businesses’ AI efforts, minimising errors in data handling.
Securing data against cyber threats is essential in the digital age, especially when managing applications at scale. According to Jaspreet Singh, founder and CEO of Druva Inc, robust cybersecurity resilience goes beyond purchasing more tools and focusing on network and vulnerability management. It involves operationalizing the tools and leveraging data as a competitive edge.
Singh points out that the increasing number of cloud and edge services are causing data to be more decentralized, making centralized data management and security essential for better understanding, breach notification, and risk assessment. AI has a crucial role to play in managing IT and data stack tasks.
Druva offers a solution to this growing issue through their software-as-a-service (SaaS) model for managing data and risk. They aim to provide predictive security in cybersecurity through the cloud’s scalability features.
To automate manual tasks, Druva launched Dru AI, which analyses logs and provides recommendations. With Dru AI, businesses receive high-fidelity data for their AI efforts. “The broader the cloud gets to the edge and other domains, the more error-prone the handling of data becomes,” Singh observed. He added that AI-based systems can bring automation and solve the long-tail problems of managing information.
In short, utilizing AI and cloud architecture for managing security and data deployment is a significant move in enhancing data protection against cyber threats and creating a competitive edge. Decentralized data make such management necessary, with AI-based systems providing the automation and error management needed.
