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Data security plays a major role in the transformation and acceleration of digital competences across every industry. But, what is data security? In simple terms, data security is how individuals and organizations protect their digital information throughout the entire data lifecycle, including generation, processing, storage, archival, and purging. These capabilities are crucial to effective ransomware protection.
To achieve this, there are many data security techniques an organization can implement to cover different critical risks and challenges of this process, such as data breaches, accidental exposure, physical security, access management, compliance and policies, among many others.
Use these links to jump down to the sections on:
- Types of Data Security
- Data Security At Rest
- Data Management and Governance
- Data Monitoring and Automation
- Conclusion
Types of Data Security
There are multiple types of data security measures and controls one should consider in order to protect digital information. The most common and important types are:
- Data encryption and masking: This enables the transformation and obfuscation of information by leveraging algorithms that make data unreadable and useless without the adequate decryption key and permissions.
- Data resilience: This mitigates the risk of accidental destruction or data loss by implementing a proper backup and recovery strategy with multiple copies of data and lifecycle rules.
- Training and awareness: Proper training is critical to educate individuals about data security features and risks such as securing the information in their machines, strengthening passwords, and using email and websites in a careful manner.
Next, we’ll go over the top three data security capabilities that every IT leader should adopt in order to accelerate their digital transformation and drive their organization towards operational excellence.
Data Security At Rest
In the past decade the amount of data created and consumed globally has grown by 5,000%. From a technology standpoint, this exceptional growth was only made possible by the massive adoption and shift towards cloud services. However, this growth also puts a huge strain on organizations when it comes to securing their data storage and managing information.
Understanding the challenges and opportunities of data security technologies at rest, as in when data is stored, is truly important to any modern IT leader. With cloud storage, one might think that cloud providers are implementing data security measures out-of-the-box on our behalf as customers. While to some extent (such as with the physical security of data centers) this is true, it’s explicit in any cloud provider shared responsibility model that information and data are always the customer’s responsibility.
Encryption, backups, and data security controls are not new groundbreaking methods and processes. However, implementing them properly has been historically challenging for many organizations, especially with on-premises servers and storage.
Cloud storage made data security easier, more affordable, and highly configurable to implement according to each organization's own requirements and expectations.
Establishing a data lifecycle automation process, creating multiple dataset replicas, and implementing customer-managed data encryption features are activities that can now be carried out with little effort and provide high business value.
Data Management and Governance
A key challenge IT leaders face is understanding what data exists across their organization and how to translate that into value for their business. Today, organizations have vast amounts of data stored across a diversity of services—self-hosted, as a service, or both.
A capability that is often underestimated when implementing data security methods is the importance of first establishing data management and governance practices across the organization. Before deciding how we should protect data, we first need to understand what data we actually have. Discovering where data is stored and what the protection requirements are is crucial to implementing proper data security controls that meet the business expectations for both compliance and organizational policies.
It’s becoming more frequent to hear news about data breaches and the exposure of sensitive information. These usually come with a tremendous monetary cost and impacts the reputation of the organizations in question. However, contrary to what people think, the most common reason for these types of events to occur aren’t sophisticated cyberattacks but rather simple storage misconfigurations and overall bad data governance.
Each organization is unique, with its own culture, processes, and requirements. Because of that, there is no standard blueprint that instructs leaders on the steps necessary to establish data management and governance practices in their organizations. However, there are data governance tools and best practices, such as foundational data governance policies, that savvy leaders know they can leverage to ease the burden of implementing data security capabilities with low operational overhead.
Data Monitoring and Automation
Establishing data security policies and guidelines that everyone in an organization should follow is a great practice that helps employees align and sets the right expectations. Still, seasoned IT leaders know that when it comes to policies and guidelines theory doesn’t always translate to practice. Modern data security needs to leverage automation and tools to make it easier to implement and ensure those policies and guidelines are actually followed in practice.
Data monitoring and automation are key modern data security capabilities that enable organizations to stay ahead of threats and proactively mitigate potential problems that arise from human errors or external attacks.
The majority of software services that organizations leverage today make it possible to easily enable out-of-the-box audit trailing and application logging. Collecting information on who did what, where, and when across an organization’s IT portfolio is now possible without significant operational oversight and costs. Naturally, this offers great potential to automate and improve an organization's data security measures.
Today, organizations can easily monitor information events and leverage tools to automate the discovery, mapping, and classification of data. Workflows can be developed to trigger in real-time and provide alerts, notifications, and immediate remediation of behaviors that deviate from the established data security policies and guidelines. A good example of this type of workflow is the automatic identification, protection, and reporting of PII (personally identifiable information) in data storage using cloud-native services.
Conclusion
While IT professionals are already familiar with concepts such as Data as a Service (DaaS) and Security as a Service (SECaaS), what the past few years have shown us is that these technologies evolved and are no longer mutually exclusive. In digital transformation and especially in software development, the tools and platforms that are capable of providing a combination of both worlds emerge as natural leaders.
NetApp products and services are a great example of a broad offering that provides out-of-the-box multiple data security capabilities. The NetApp Ransomware Protection is a comprehensive set of data-centric capabilities designed to protect your digital information using a zero-trust approach.
Mapping and classification of data, detection of anomalous user activity, access management, and rapid backups and restores are just a few examples of the many data security features offered in NetApp Ransomware Protection.
Schedule a call with us to learn more about ransomware protection and other data security capabilities NetApp solutions can offer.
