Intelligent data management is an AI-powered and automated way to store, identify, and protect enterprise data across hybrid and multicloud environments with minimal IT effort. Not only does this save time and money while reducing enterprise risk, but it can help unlock latent value in data—which is arguably an organization’s most valuable asset—to drive competitive advantage.
Why Is Intelligent Data Management Important?
IT environments over the last decade have undergone a remarkable evolution. From on-premises data centers to virtualized servers, hyperconverged hardware, Software as a Service (SaaS) applications, and now multiple clouds, modern IT infrastructure has become more complex and siloed than ever.
All this has complicated organizations’ ability to manage increasing data volumes effectively. Because of data sprawl, the daily enterprise IT requirement to protect, store, identify, and provision data is an inefficient and costly process.
For many teams, important operations—backup, managing unstructured data, disaster recovery (DR), security, governance, dev/test, and analytics—are taking too long to perform because of legacy data management tools. Organizations’ astonishingly rapid move first to cloud, and now multicloud, only complicates the matter.
Siloed legacy products not only cause mass data fragmentation but introduce a wider attack surface for cybercriminals to exploit. Multiple entry points and copies of data are ripe for ransomware attackers seeking to not only encrypt data but exfiltrate it in double extortion schemes for financial gain.
Taking advantage of an intelligent data management platform is an AI-powered and automated way for organizations to eliminate data management chaos. Intelligent data management simplifies tasks and brings together multiple data sources—structured, semi-structured and unstructured for the purposes of deriving greater insights from all data and proactively defending data from bad actors.
For example, AI-based anomaly detection integrations can identify cyber threats lurking in backups or unstructured data. Smart, built-in recommendation systems can proactively avert potential issues while predicting problems and trends, allowing IT and security teams to cover more ground while keeping their nights and weekends free. If there is an impending threat, intelligent data management can help root it out or begin remediation efforts, speeding recovery time objectives (RTO).
Intelligent data management puts IT back in control and finally frees the business to extract the value it needs from its vast troves of information.
What Is an Intelligent Data Platform?
An intelligent data platform helps enterprises across industries simplify and improve their data management strategies. It automates the convergence of structured, semi-structured and unstructured data sources into a single environment without duplicating data. From there, teams across the business can use artificial intelligence and machine learning (AI/ML) to make data more valuable by uncovering insights from it. They can also run third-party applications on the data (moving the data to compute resources) to discover vulnerabilities.
What Is an Intelligent Data Management Framework?
An intelligent data management framework works by consolidating all data sources—unstructured, semi-structured and structured—onto a platform with built-in smarts for automating the delivery of insights and recommending remediation, as needed, for example in response to a ransomware attack.
How Many Intelligent Data Management Systems Are There?
A significant number of data management systems have emerged in recent years, yet very few of them are truly “intelligent.” Those that are AI-powered are smartest, leveraging AI fully to automate the entire data management lifecycle for all types of data sources.
To ensure you choose the right intelligent data management system, you need to make sure that it is AI-powered while:
Converging all data sources—structured, unstructured, and semi-structured data sources—to eliminate data silos in your business
Leveraging the hyperscale architecture to scale as needed without having to stop and provision, set up, and manage additional infrastructure
Supporting a hybrid cloud environment that enables you to control all your data management from one location with a single, intuitive console
Of all the intelligent data management software that is emerging on the market, you need to deploy a cloud-based one that uses AI to perform data monitoring of data flow and security, including ransomware, enabling applications to run faster, reducing development cycles, and increasing data productivity and value.
How Much Intelligent Data Management Do I Need?
Intelligence is not about scale. Organizations need modern intelligent data management capabilities to help teams work smarter, not harder. With intelligent data management, organizations can improve decision making and jumpstart threat response.
For example, AI-based threat visibility lets IT monitor and detect anomalies that may be the start of a ransomware attack. Automated alerting and AI connections to other software solutions can help unite response, too.
Proactive recommendations from intelligent data management platforms are ideal for monitoring, modeling, and optimizing operations, too. Teams can use these predictive analytics to spot trends early and plan ahead for change.
Finally, an intelligent data management platform saves IT time by automating manual, time-consuming tasks and when there is a problem, improve recovery time objectives.
Cohesity and Intelligent Data Management
Today’s highly fragmented and siloed way of managing increasing volumes of data makes it difficult—if not impossible—to get a comprehensive picture of all the information an organization possesses. It has traditionally been housed across different data centers, and, increasingly, the cloud and even multiple clouds. This results in disparate silos of data for different operations. And it has created enormous challenges for companies needing to protect data, back it up, and perform comprehensive analyses across all the isolated infrastructure stacks, not to mention defend data against increasingly sophisticated ransomware attacks.
To drive intelligent data management forward, Cohesity considered the principles of modern software, particularly of hyperscalers and their use of AI.
Rather than simply improve on the legacy data management framework, Cohesity introduced next-gen data management. This new approach completely redefines and transforms data management from a disparate collection of isolated parts serving different silos to a fully integrated, consolidated hybrid cloud solution capable of managing all data from a central location. And it’s powered by AI insights.
Cohesity advances intelligent data management platform concepts, using AI to automate manual efforts and trigger proactive alerts and health checks. AI-based threat detection thwarts cyberattacks, particularly ransomware. And AI-powered recommendations reduce IT’s operational burden while boosting cyber resiliency.
Powered by AI insights is a core tenet of Cohesity next-gen data management, which features:
Simplicity at scale — Cohesity consolidates siloed data management functions onto a single and scalable software platform capable of running multiple use cases at scale, slashing complexity and cost. As a comprehensive global solution, the entire data management lifecycle can be managed from a single, intuitive console.
Zero Trust security — Cohesity put security first when designing its new data management platform. A hyperscale file system spans core to edge, giving organizations total visibility and control over data. Built upon the principles of least privilege and segregation of duties, Cohesity’s multilevel security protections are granular, proven, and world class.
Powered by AI insights — Cohesity features AI-based anomaly detection, risk posture assessments, predictable recovery, deep visibility, and leading security integration capabilities, enabling companies to combat cyberthreats from inside and outside of their organization. Built-in AI-based recommendation systems proactively avert potential issues and help teams spot problems before they impact users. Finally, Cohesity AI and machine learning capabilities help IT staff cover more ground without negatively impacting their nights and weekends.
Third-party extensibility — Cohesity is an efficient platform with APIs for integrating third-party and Cohesity apps—including automation and orchestration tools. This drives deeper data security, cost, compliance, and value visibility.