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How Next-Gen Data Management Can Help You Navigate the Hybrid Multicloud World

Chris Wiborg
Cohesity

Once upon a time data lived in the data center. Now data lives everywhere.

You have data in the data center, data at edge locations used by remote offices, data on mobile devices, and data in the cloud. And when a business has data in the cloud, it usually doesn't mean just one cloud.

Chances are good that you have data in SaaS applications like Microsoft 365, Salesforce, and other applications, clouds, and systems. Organizations are increasingly adopting hybrid multicloud strategies. So, some of your data might live on AWS, Google Cloud Platform, and/or Microsoft Azure.

All this signals the need for a new approach to data management, a next-gen solution — one that gives the power of choice to an organization to design a data management strategy that best meets its unique business needs. At the same time, the entire process of data management must be simplified. The era of multiple legacy point solutions to handle a company's data needs cannot meet the needs of a modern enterprise that must manage, protect, and derive business value from its data to compete and succeed.

Understand That Distributed Data Creates New Mobility and Security Implications

When your data lives in many different places, there are several implications.

You need to address data logistics — or how to get data from one place to another. In some cases you are moving data to the cloud. But sometimes you may want to repatriate data, which involves moving data back from the cloud.

Additionally, you have to rethink your approach to security. When all of your data lived in your data center, you could protect it with a hard perimeter around that data center. But because data is now everywhere, your security model must change and adopt zero trust principles.

Now you need to manage data everywhere in a way that is efficient and effective. Your data management approach should start with protecting and backing up your data. This will help you to recover if you have an outage or you are attacked by ransomware, which is growing at an alarming rate.

Take Responsibility Rather Than Assuming That Data in the Cloud Is Safe

You may think that when you put data in the cloud it is automatically protected. But just because your Microsoft 365 implementation is in the cloud, it doesn't mean Microsoft can bring back your data if things go wrong. Microsoft 365 retains customer content for 30 days at most.

Microsoft, Google, and AWS may offer guarantees related to their cloud services' uptime and availability. But you are responsible for making sure your data is secure and accessible for compliance, legal, and other purposes. This is known as the cloud's shared responsibility model. Under this model, you are responsible for your data — even if an employee mistakenly or intentionally deletes that data or you fall victim to ransomware or another type of cyberattack.

But not everybody operating in today's hybrid multicloud world understands that because SaaS and IaaS are relatively new models, and many IT operations teams and other talent responsible for resiliency aren't fully aware of the limitations and risks cloud poses when it comes to your data.

Avoid Creating More Silos By Taking a Centralized Approach

Your database provider may tell you that its database provides native online backup. But that is a siloed approach that adds complexity from a broader operations perspective rather than enabling modernization and simplification.

The best way to avoid silos is to implement a centralized data management solution that protects and lets you manage your data — in the cloud and on premises — using a single administrative interface.

Be Aware That As-A-Service Disaster Recovery Is An Effective Option

You may choose to back up all of your cloud, software-as-a-service, and on-premises data using a self-managed backup solution. But now data management companies also offer additional resiliency via disaster recovery-as-a-service (DRaaS) solutions. This means you now have the flexibility to choose between managing everything on your own or letting your DRaaS provider focus on managing the infrastructure, while you focus on the policies that will govern your data — where the value resides.

Whether you choose to manage your own infrastructure, consume as-a-service options, or adopt a flexible hybrid approach — as more and more organizations are choosing — make sure that your data management solution addresses all of your needs, wherever your data resides.

By consolidating "one off" solutions and adopting a next-gen data management platform approach you can simplify complexity and lower the costs involved with managing your data. At the same time, this approach will allow you to follow an operational strategy that is best for your business while helping you to avoid data mobility problems, and letting you recover faster when disaster strikes.

Now you can more easily protect your data. More importantly, you can protect your business.

Chris Wiborg is VP of Product Marketing at Cohesity

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How Next-Gen Data Management Can Help You Navigate the Hybrid Multicloud World

Chris Wiborg
Cohesity

Once upon a time data lived in the data center. Now data lives everywhere.

You have data in the data center, data at edge locations used by remote offices, data on mobile devices, and data in the cloud. And when a business has data in the cloud, it usually doesn't mean just one cloud.

Chances are good that you have data in SaaS applications like Microsoft 365, Salesforce, and other applications, clouds, and systems. Organizations are increasingly adopting hybrid multicloud strategies. So, some of your data might live on AWS, Google Cloud Platform, and/or Microsoft Azure.

All this signals the need for a new approach to data management, a next-gen solution — one that gives the power of choice to an organization to design a data management strategy that best meets its unique business needs. At the same time, the entire process of data management must be simplified. The era of multiple legacy point solutions to handle a company's data needs cannot meet the needs of a modern enterprise that must manage, protect, and derive business value from its data to compete and succeed.

Understand That Distributed Data Creates New Mobility and Security Implications

When your data lives in many different places, there are several implications.

You need to address data logistics — or how to get data from one place to another. In some cases you are moving data to the cloud. But sometimes you may want to repatriate data, which involves moving data back from the cloud.

Additionally, you have to rethink your approach to security. When all of your data lived in your data center, you could protect it with a hard perimeter around that data center. But because data is now everywhere, your security model must change and adopt zero trust principles.

Now you need to manage data everywhere in a way that is efficient and effective. Your data management approach should start with protecting and backing up your data. This will help you to recover if you have an outage or you are attacked by ransomware, which is growing at an alarming rate.

Take Responsibility Rather Than Assuming That Data in the Cloud Is Safe

You may think that when you put data in the cloud it is automatically protected. But just because your Microsoft 365 implementation is in the cloud, it doesn't mean Microsoft can bring back your data if things go wrong. Microsoft 365 retains customer content for 30 days at most.

Microsoft, Google, and AWS may offer guarantees related to their cloud services' uptime and availability. But you are responsible for making sure your data is secure and accessible for compliance, legal, and other purposes. This is known as the cloud's shared responsibility model. Under this model, you are responsible for your data — even if an employee mistakenly or intentionally deletes that data or you fall victim to ransomware or another type of cyberattack.

But not everybody operating in today's hybrid multicloud world understands that because SaaS and IaaS are relatively new models, and many IT operations teams and other talent responsible for resiliency aren't fully aware of the limitations and risks cloud poses when it comes to your data.

Avoid Creating More Silos By Taking a Centralized Approach

Your database provider may tell you that its database provides native online backup. But that is a siloed approach that adds complexity from a broader operations perspective rather than enabling modernization and simplification.

The best way to avoid silos is to implement a centralized data management solution that protects and lets you manage your data — in the cloud and on premises — using a single administrative interface.

Be Aware That As-A-Service Disaster Recovery Is An Effective Option

You may choose to back up all of your cloud, software-as-a-service, and on-premises data using a self-managed backup solution. But now data management companies also offer additional resiliency via disaster recovery-as-a-service (DRaaS) solutions. This means you now have the flexibility to choose between managing everything on your own or letting your DRaaS provider focus on managing the infrastructure, while you focus on the policies that will govern your data — where the value resides.

Whether you choose to manage your own infrastructure, consume as-a-service options, or adopt a flexible hybrid approach — as more and more organizations are choosing — make sure that your data management solution addresses all of your needs, wherever your data resides.

By consolidating "one off" solutions and adopting a next-gen data management platform approach you can simplify complexity and lower the costs involved with managing your data. At the same time, this approach will allow you to follow an operational strategy that is best for your business while helping you to avoid data mobility problems, and letting you recover faster when disaster strikes.

Now you can more easily protect your data. More importantly, you can protect your business.

Chris Wiborg is VP of Product Marketing at Cohesity

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Payment system failures are putting $44.4 billion in US retail and hospitality sales at risk each year, underscoring how quickly disruption can derail day-to-day trading, according to research conducted by Dynatrace ... The findings show that payment failures are no longer isolated incidents, but part of a recurring operational challenge that disrupts service, damages customer trust, and negatively impacts revenue ...

For years, the success of DevOps has been measured by how much manual work teams can automate ... I believe that in 2026, the definition of DevOps success is going to expand significantly. The era of automation is giving way to the era of intelligent delivery, in which AI doesn't just accelerate pipelines, it understands them. With open observability connecting signals end-to-end across those tools, teams can build closed-loop systems that don't just move faster, but learn, adapt, and take action autonomously with confidence ...

The conversation around AI in the enterprise has officially shifted from "if" to "how fast." But according to the State of Network Operations 2026 report from Broadcom, most organizations are unknowingly building their AI strategies on sand. The data is clear: CIOs and network teams are putting the cart before the horse. AI cannot improve what the network cannot see, predict issues without historical context, automate processes that aren't standardized, or recommend fixes when the underlying telemetry is incomplete. If AI is the brain, then network observability is the nervous system that makes intelligent action possible ...

SolarWinds data shows that one in three DBAs are contemplating leaving their positions — a striking indicator of workforce pressure in this role. This is likely due to the technical and interpersonal frustrations plaguing today's DBAs. Hybrid IT environments provide widespread organizational benefits but also present growing complexity. Simultaneously, AI presents a paradox of benefits and pain points ...

Over the last year, we've seen enterprises stop treating AI as “special projects.” It is no longer confined to pilots or side experiments. AI is now embedded in production, shaping decisions, powering new business models, and changing how employees and customers experience work every day. So, the debate of "should we adopt AI" is settled. The real question is how quickly and how deeply it can be applied ...

In MEAN TIME TO INSIGHT Episode 20, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA presents his 2026 NetOps predictions ... 

Today, technology buyers don't suffer from a lack of information but an abundance of it. They need a trusted partner to help them navigate this information environment ...

My latest title for O'Reilly, The Rise of Logical Data Management, was an eye-opener for me. I'd never heard of "logical data management," even though it's been around for several years, but it makes some extraordinary promises, like the ability to manage data without having to first move it into a consolidated repository, which changes everything. Now, with the demands of AI and other modern use cases, logical data management is on the rise, so it's "new" to many. Here, I'd like to introduce you to it and explain how it works ...

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