Meeting Tomorrow’s Data Challenges with AI Insights Today
Enterprises can’t protect their data from cyber threats they can’t see coming. With the increasing blast of ransomware, it’s no wonder business leaders are growing more concerned about their inability to predict where or which IT assets will be compromised in the event a vulnerability is exploited.
Protecting data is just one of the data management tasks IT teams must perform. While they’re detecting and mitigating threats, they’re also performing routine backup and recovery, data governance, file and object services, and data analytics. Every manual process IT pros must undertake with legacy products takes away money and resources they could be focusing on higher-level innovation.
At a time when 86% of enterprises believe an IT talent shortage is having a negative impact on their ability to support business transformation, they’re looking for a next-gen data management solution that consolidates environments, reduces complexity, and increasingly automates critical data management tasks.
The Time is Now for AI and Automation
Artificial intelligence (AI), analytics, and automation are expected to be the top three tech investment themes for enterprises in 2022, according to a recent Everest Group report. Seven in ten surveyed organizations (70%) say they will actively increase their adoption of automation going forward.
When it comes to AI and data security alone, Everest Group analysts write “[Enterprises] need to adopt a platform that can quickly detect vulnerabilities using [machine learning] algorithms and help them react, mitigate, and recover from these attacks.”
A next-gen data management platform powered by AI insights improves decision-making and allows enterprises to act faster. With built-in intelligence, the platform proactively alerts IT of potential issues and predicts future trends. In doing so, it allows IT staff to accomplish more during regular working hours.
“Think about everyone working in IT today,” says Cohesity CEO and Founder Mohit Aron. “They’re working harder and harder. We want them working smarter.”
A next-gen data management platform with AI-powered insights delivers:
AI-based threat visibility – It monitors and detects anomalies that can signal ransomware attacks. By seamlessly sharing this intelligence with security information and event management (SIEM) and security orchestration, automation and response (SOAR) solutions, the data management platform helps unite operational teams, further maximizing efficiency.
Proactive recommendations – It includes capabilities to monitor, model, and optimize operations. Through predictive analytics, the solution can assess trends and plan for growth as enterprises embrace hybrid environments while consolidating distributed data silos into one hyperscale platform.
Smart operations – By leveraging AI and machine learning (ML) techniques to automate repetitive tasks, it roots out problems and errors as well as speeds remediation processes.
AI-Powered Insights from Modern Data Management in the Real World
Novartis Institutes for BioMedical Research, the scientific-research arm of the large pharmaceutical company, has embraced cloud technologies to modernize its IT and deployed Cohesity next-gen data management for backup and recovery. It now seamlessly replicates data to Amazon Web Services (AWS) for archival and has cut its data management costs by 50%, improved efficiency, and regained staff time for innovation.
“Cohesity was a single, web-scale solution supporting multi-cloud, so we leaned toward it,” said Amit Singh, senior storage architect at Novartis. “[We could gain] not only cost savings but efficiencies that would allow IT staff to work on additional high-priority projects.”
With its previous solution, Novartis IT had to manually manage 40 – 50 backup policies, run scripts, and regularly troubleshoot backups. Today, IT automatically manages more than 3 petabytes of backup data with just a handful of automated policies. For example, proactive anomaly detection built into the platform alerts IT to investigate suspicious data patterns before they become a problem.
“Moving to the cloud is one thing,” says Singh, “But if your data increases tomorrow, how do you sustain that growth?”
Driving Insights With Algorithms
AI-enhanced algorithms make it easier to monitor, plan, and optimize operations in today’s distributed IT environments. They constantly learn and adjust, averting potential issues and providing predictive analytics-based alerts, such as capacity utilization trends and proactive wellness checks.
Similarly, AI-based data security helps detect cyberthreats without consuming precious resources on production systems. From there, an AI-powered insights platform issues alerts of potential danger and initiates counter measures automatically, such as recommending a clean backup snapshot for restore in the event of a ransomware attack.
“The platform should be able to detect any threats itself, based on machine-learning and AI,” explains Aron. “It should give you proactive recommendations and notifications. If there’s an attack, it should be able to inform you there was an attack, and if there’s something wrong in the platform, it should proactively tell you about that.”
AI plays a huge role in handling exploding volumes of data and all the security threats and management tasks that come with it.
To learn how next-gen data management incorporates AI-powered insights, visit Cohesity.