Dark data, often defined as unstructured information that organisations collect but fail to use effectively, poses significant challenges for businesses aiming to leverage artificial intelligence (AI) technologies. This unutilised data, typically scattered across various IT infrastructures, can turn into a liability if not managed properly, making organisations vulnerable to cyberattacks and compliance issues.
In a recent interview with Business Today, Sathish Murthy, Senior Systems Engineering Lead for Cohesity in ASEAN and India, shed light on the significant challenges organisations face regarding dark data and the adoption of artificial intelligence (AI) technologies.
What is Dark Data?
Murthy explained that dark data, which encompasses unstructured information often siloed within IT infrastructures, can transform from a valuable asset into a liability if not managed properly.
“When data is fragmented across multiple locations without central visibility, it creates ‘dark data,'” he noted.
This lack of clarity poses serious risks for organisations, making them vulnerable to cyberattacks, particularly ransomware. He emphasised that effective data management and classification are essential to mitigate these risks.
The concept of cyber resilience emerged as a critical theme in the discussion. Murthy pointed out that organisations must focus on maintaining their business processes despite adverse cyber events.
“Cohesity’s AI-powered data security platform supports a zero-trust architecture, which is vital for preserving business continuity and reputation,” he said.
Prioritising Data Management for AI Readiness
When it comes to making backup data AI-ready, Murthy identified data indexing and instant searchability as vital components. “AI-readiness hinges on structured and searchable data,” he explained, highlighting the challenges organizations face with outdated data management systems.
He urged organisations to prioritise data aggregation and unification to eliminate silos and optimise their data holdings.
Overcoming Barriers to AI Adoption with Cohesity’s GAIA
Murthy also discussed other barriers to AI adoption, notably the quality of training data. “Biased or incomplete data can lead to erroneous results,” he cautioned.
Moreover, he criticised the trend of “AI washing,” where vendors oversell AI capabilities that deliver limited insights. In response, Cohesity has introduced GAIA, an AI-powered enterprise search assistant that enhances data retrieval capabilities.
Real-world use cases demonstrate the potential of AI in overcoming these challenges.
For instance, Murthy described how AI-powered search assistants enable organizations to assess their cyber resilience by simplifying data retrieval.
This approach allows teams to quickly access valuable insights, significantly enhancing operational efficiency.
Cohesity’s commitment to addressing dark data challenges is evident in its modern data management solutions. “Our Cohesity Data Cloud not only reduces the presence of dark data but also encrypts and ensures the immutability of data backups,” he noted.
This comprehensive approach equips organisations to respond effectively to regulatory and compliance needs while safeguarding sensitive information.
Shaping the Future of AI in Malaysia
Looking to the future, Murthy envisions a transformative impact of AI technologies across various sectors. “AI and machine learning will profoundly influence how companies and individuals interact with technology,” he remarked. However, he cautioned that for AI to reach its full potential, it must be integrated correctly into existing systems and fed accurate data.
As Malaysia actively pursues AI adoption strategies, Murthy believes Cohesity can play a pivotal role. “We help organizations become AI-ready and leverage their data through our generative AI platform,” he concluded. This support is crucial as businesses navigate the complexities of data management and aim to harness AI’s transformative capabilities.
