The integration of artificial intelligence (AI) and the Internet of Things (IoT) has led to a surge in data volume, prompting significant shifts in information management strategies.
Taylor Lowe, the CEO, and founder of AI system software Metal, highlighted the extensive investments made by the financial industry over the past decade in data research and the development of data knowledge departments. According to Lowe, the shift towards a data-centric approach has yielded substantial benefits, with AI and similar technologies amplifying the insights derived from data.
Nevertheless, this data deluge has posed formidable challenges for security teams, particularly in distinguishing between threat detection, data exploration, and classification. Research by cybersecurity firm Rubrik indicates that 98% of businesses are struggling with data visibility issues stemming from intricate technology setups that malicious actors can exploit.
In response to these challenges, CrowdStrike and Rubrik have joined forces to empower security professionals with the tools and environment needed to swiftly preempt data breaches. Daniel Bernard, the chief business officer at CrowdStrike, emphasized the significance of this collaboration in fortifying threat detection capabilities through the integration of data discovery, classification, and backup services.
Anneka Gupta, the principal product representative at CrowdStrike, underscored the inadequacy of traditional backup solutions in combating modern cyber threats, advocating for a proactive approach to bolster cyber resilience and thwart adversarial activities.
Furthermore, Lowe proposed harnessing artificial intelligence and large language models (LLMs) to parse through unstructured internal data, which constitutes a substantial portion of global data repositories. By providing strategic direction, LLMs can effectively analyze unstructured data, informing the development of tailored data use cases crucial for software implementation.
The successful deployment of software that maximizes existing data assets to streamline customized workflows hinges on establishing a robust infrastructure capable of facilitating data transformation, storage, and retrieval. Lowe emphasized the synergy between these two components as the key to unlocking substantial productivity enhancements in data-driven operations.
