What Is Cloud Data Protection? Definition, Importance, and Best Practices
Cloud data protection focuses on protecting data that is stored, managed, and manipulated in a cloud environment.
Cloud data protection is defined as a data protection model that focuses on protecting organizational data that is stored, manipulated, and managed in a cloud or hybrid environment. The model requires many data policies, strategies, and solutions to work in tandem. In this article, we explain what cloud data protection is, its importance for enterprises followed by comprehensive best practices for 2021.
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What Is Cloud Data Protection?
Cloud data protection is a data protection model that focuses on organizational data that is stored, manipulated, and managed in a cloud or hybrid environment. The model requires many data policies, strategies, and solutions to work in tandem.
Data protection is the process of protecting an organization’s data from compromise, loss, or theft. While traditional data protection models work well for simple on-premise deployments, they can get complicated with data housed in cloud or hybrid environments. This article focuses specifically on cloud data protection.
When experts talk about data protection, it encapsulates:
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- Data protection: Dealing with the loss of data by looking into backup and recovery systems and processes.
- Data security: Dealing with safeguarding company and customer data from internal and external threats.
- Data privacy: Dealing with control and management access for different data segments so that only the right people can access appropriate information.
Cloud data protection models also need to accommodate different categories of data that organizations typically work with. These include public data, internal company data that only employees have access to, sensitive data that can be anything from employee payroll information to customer social security numbers, and restricted data that is controlled by government regulations.
IT and DevOps teams have a bird’s eye view of data when an organization’s infrastructure is entirely on-premise. However, this is not the case when cloud vendors are involved, especially with public clouds.
Cloud vendors operate using the ‘shared responsibility’ model. This means that while cloud vendors take responsibility for protection scenarios such as backup and recovery, customers (organizations) are responsible for securing their own data and traffic.
Moving to the cloud does reduce overheads, but it comes at the expense of control. Organizations must rely on vendors to keep the underlying physical hardware and network secure. Although vendors provide a set of security policies and controls, a chunk of the scope of security remains with them.
Today, infrastructure is built across multiple platforms, services, and third-party applications. There may be multiple cloud vendors involved in a single setup. This means that there is inconsistency in the way data is stored, managed, and secured. Integration between these multiple components must be seamless at the data protection level as well.
These challenges signal the need for a consistent and unified data protection strategy or solution. That’s where data protection models come into the picture.
Also Read: Top 10 Cloud Data Protection Companies in 2021
Importance of Cloud Data Protection for Companies
Organizations have been increasingly recognizing the cost-effectiveness and ease of operation that comes from moving infrastructure and assets to the cloud, or at least a hybrid environment. In fact, even five years ago, cloud traffic was estimated at 3,851 exabytes.
The pandemic only accelerated the adoption of cloud by organizations of all sizes. Gartner’s research shows that this surge in cloud adoption may lead to 94% of company workload being processed by cloud data centers by the end of 2021.
Importance of Cloud Data Protection
As the number of remote workers increases, so does the need for protecting access and movement of company data across various known and unknown networks. A robust cloud data protection model serves to:
1. Maintains data visibility
Most organizations have data flowing and stored across multiple clouds, services, and applications. It is easy for segments of data to fall through the cracks with so many players involved. A good cloud data protection model begins with a map of every single piece of data, which is reiterated periodically. This allows for better data hygiene and even helps cut down data storage costs by identifying non-essential data.
2. Ensures data integrity
In today’s landscape, data can make or break a company’s success. So, data should be accurate, complete, and reliable at any point in its lifecycle. This is why cloud data protection makes sense. One of the inherent goals of cloud data protection is to ensure that no data within the company is outdated, manipulated, or lost.
3. Maintains compliance
Compliance regulations vary based on the location of the data. Cloud vendors are responsible for implementing compliance-related policies. But it is the customer organization that is audited for compliance. This means that organizations must have this information from all cloud integrations, and it must be transparent and clear enough for both external and internal audits.
In fact, ‘data protection’ gained a lot more importance when general data protection regulation (GDPR) came into force in mid-2018. It was one of the many regulations passed to ensure the privacy and security of organizational data, especially from the customer’s perspective. Any company using cloud vendors is viewed as a ‘data controller’. The company is responsible for how the data is handled and not the vendor.
Every data controller must ensure:
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- All company data containing PII that is processed on the cloud is secure.
- Data can only be transferred from the EU area to a preapproved area with similar levels of protection.
- SLAs for high levels of data protection from the cloud provider.
Failure to comply with these laws could result in lawsuits and hefty fines by the state.
Also Read: What Is Cloud Encryption? Definition, Importance, Methods and Best Practices
4. Ensures data security
Another plus of data protection on the cloud is the systematic definition of unifying policies applied across all layers. Policies about data storage, data dictionary, access rules, and role-based permissions prevent any form of intrusion, keeping sensitive data secure.
Cloud data protection models typically secure data across multiple environments by providing the means to encrypt and monitor data in every file and at every user level. This visibility helps IT staff and DevOps teams seize control of the complex setup.
Cloud data protection offers a step-by-step strategy to eliminate any threats to company data. Contemporary cloud data protection solutions also identify risks and data anomalies proactively, allowing security teams to shut down any attempts of cyber-attacks or malware injection.
5. Manages data storage
A cloud data protection model provides a centralized way to monitor and access data across the cloud infrastructure. This means logging and reporting every data access and manipulation. This allows IT teams to identify and kill rogue and suspicious data while ensuring that the data segments are stored with appropriate controls in place, based on the category they fall under.
6. Helps outline a disaster recovery plan
Technically, a disaster recovery plan comes under an organization’s business continuity plan. But it is also one of the prescribed goals of the data protection process. Cloud data protection processes allow for:
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- Backup: A backup copy is the image of the live copy of data that currently runs the entire system. It is used whenever an application or a system needs to be rebooted.
- Recovery: This involves the recovery of the data and the servers and networks that enable the flow of this data, thus maintaining data integrity and consistency.
- Availability: Every data protection plan must factor in the maximum downtime that a system can take without affecting daily business operations. This metric is met by keeping the systems highly available, often with similar and redundant infrastructure components in place.
Building a cloud data protection model pushes companies to address their DRP solutions. It only makes sense that DRP activities fall under data protection since the first step of cloud data protection is to identify critical data assets.
7. Helps make informed decisions
One of the advantages of having an aerial perspective of data is that key aspects of this data can be identified and molded to meet business needs. It can enable leadership to make informed decisions, marketing teams to hone their target research, and finance teams to improve operational costs.
With the benefits of a cloud data protection model far outweighing the challenges of moving to cloud-based or hybrid solutions, it is not surprising that the data protection market is estimated to exceed $158 billion by 2024.
Also read: What Is Disaster Recovery? Definition, Cloud and On-Premise, Benefits and Best Practices
Top 7 Best Practices and Policies for Cloud Data Protection in 2021
As discussed above, the best cloud data protection plans begin with policies decided by all the data stakeholders. Besides these tailored policies, here are a few other things that can elevate cloud data protection in your organization:
Best Practices for Cloud Data Protection in 2021
1. Ensure built-in security at all stages
The data protection solution must ensure that all stored data is encrypted. Vendors must have SLAs that confirm data protection measures. Even with cloud vendor-assured encryption, an additional level of security can be created by encrypting at the file level. This involves encrypting the data even before sending it out to be stored on the cloud.
Another security measure is sharding the data to be stored at multiple location points. This makes it difficult for hackers to obtain entire chunks of data, with only fragments at their disposal. Point-to-point data transfer can also be bolstered by additional encryption with the traditional SSL.
2. Create centralized control
Consistency is the key to cloud data protection. All user and application access across any level of the system must go through this component. This can be done with the help of an IAM or a PAM solution.
Access rule policies must be established. Good cloud data protection also looks for context-based behavioral changes. This means that it allows access to a known user based on other factors such as time of the request, location of request, etc. MFAs must be put in place, especially where sensitive and restricted data is concerned. Data policies must be established with the possible implementation of a data governance tool.
Centralized monitoring must also allow the IT team to spot shadow IT, which is quite common with cloud deployments. Clouds make it easy to start up, configure, and run third-party services, allowing many rogue systems to use cloud resources.
Also read: What Is Data Governance? Definition, Importance, and Best Practices
3. Provide a stable and robust user experience
It is easy to go overboard with security while pausing and diverting each bit of data in the system’s traffic. This drives up internet bandwidth usage and may result in slower application performance.
The SASE framework defined by Gartner recommends that data protection engines should be placed closer to the user level to prevent backhauling. The cloud data protection model must produce an optimal balance between usability and security.
4. Automate where possible
Competitive cloud vendors now provide built-in algorithms to identify possible vulnerabilities. They use AI to aid this process. Automated patch creation based on identified risks are a huge boon to the IT team.
Automated log and report generation also allows security teams to spot suspicious behavior with respect to data access and manipulation. This also helps with compliance audits. Security updates must also be automated and configurable.
5. Document the organization’s responsibility
There is room for confusion in the shared responsibility model in terms of responsibilities. Organizations must go through their SLAs with cloud providers with a fine comb. Ideally, the provider ensures hardware and software security while the organization is responsible for its own data assets.
Edge cases, such as protocol in case of a data breach, must also be established with the cloud vendor. All of this must be documented in a transparent and accessible manner, ensuring that concerned employees are well aware of their responsibilities. This also comes in handy during compliance audits.
Also Read: Top 10 Cloud Security Challenges 2021 Needs to Address
6. Ensure compatibility
Every organization needs a single data protection platform that supports both on-premise and cloud solutions. This makes it more scalable. Multi-cloud deployments require a cloud data protection plan that must address data challenges across multiple applications and deployments. For example, a secure web gateway cannot be the only solution in place. A cloud access security broker may also be required to secure SaaS applications.
The very nature of the cloud implies integration and transfer of data between multiple services, both internal and third-party. A cloud data protection plan must make sure that there are no security gaps in the integration. The organization must pick up the security measures that the service vendor does not fulfill.
7. Ascertain backup and recovery
Once data security and privacy have been covered, data protection comes into play. Data must be replicated and stored at a secondary location, allowing businesses to bounce back in case of any interruption. The organization’s disaster recovery metrics, such as recovery time objectives (RTOs) and recovery point adjectives (RPOs), must align with what the cloud vendor provides. These should be built right into the SLAs.
Also Read: What Is Data Security? Definition, Planning, Policy, and Best Practices
In conclusion
IDG’s 2020 Cloud Computing Survey revealed that more than 75% of IT spending is now toward the cloud. The survey also showed that around 92% of organizations are working on cloud in some way or another. So, it is high time that organizations start taking cloud data protection seriously.
However, it’s important to note that for a cloud data protection plan to be truly effective, it must be tailor-made for the organization, keeping scalability in mind. While it may seem daunting at first, the fiscal, operational, and reputational benefits are too many to ignore. If your organization lacks the resources to create a cloud data protection plan, it can explore data protection as a service (DPaaS) for expert support.
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