Dave Albano, President and CEO of RestorePoint.ai, has more than 35 years of technology industry leadership experience. Read Dave Albano's full executive profile here.
As organizations look to build out more complex digital frameworks, breaking down data silos is essential. But there’s a catch: As data analysts, data scientists and others work across various groups, disciplines and systems, security risks inevitably increase.
In this dynamic data management and AI ecosystem, the challenge becomes how to maximize data flexibility and security. One approach revolves around a modern data architecture that makes it possible to apply purpose-built analytics and AI tools to the metadata repository. This centralized approach can improve threat detection and offer new ways to address cybersecurity risks.
Data lakes differ significantly from traditional databases in their structure, data handling and use cases. Traditional databases use a schema-on-write approach, storing structured data in a predefined relational model, which is ideal for transactional systems requiring quick query responses and data integrity.
For companies that have already implemented a modern data architecture to extract business value from their information assets, using this infrastructure to support security operations offers a prebuilt framework to provide the deep visibility and automation needed to manage security in an increasingly complex digital landscape.
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