Next-Gen Storage: A Building Block for Digital Transformation

Featured article by Richard Diver, Cloud Security Architect, Insight Enterprises

Organizations today need to take an entirely different approach to data storage than they did in the past. The age of monolithic storage arrays of spinning disks in data centers is quickly fading away. Without reevaluating storage strategy, organizations might miss out on the true benefits of digital transformation.

Storage decisions in many ways have become far more complex while new technologies and delivery models enabled by the cloud and edge computing have created new opportunities for greater efficiency, performance, and security.

The key to success in this new IT environment is knowing how to effectively and securely manage a variety of data storage resources which typically comprise the modern digital enterprise.

Organizations need to define storage goals and requirements, which are driven by real business objectives and security. That means figuring out which use cases are most important and where risk exists, and then designing a storage architecture that will support those use cases while minimizing risks.

It is easy to fall into the trap of singling out one or two use cases at the expense of all others. The data storage team needs to be aware of the needs of users across the entire organization, as well as to regularly liaise with information security. The storage architecture and solutions deployed should be applicable to as many business processes as possible so that different departments and groups can meet their needs securely and without introducing risk of data breach, theft, or compliance issues. Centralizing the design process and requirements gathering improves standardization and cohesiveness, and reduces wasteful spending.

As part of building the data storage strategy, keep in mind the variety of business processes within the organization. For example, what will the storage needs be going forward for areas such as marketing and sales, research and development, human resources, product design and development, manufacturing, customer experience, finance. How about different technology initiatives planned by IT and business groups, such as big data/analytics projects, increased high-quality video capture and storage, Internet of Things (IoT) initiatives, artificial intelligence/machine learning, autonomous vehicles, blockchain?

Those responsible for updating and maintaining the data storage infrastructure at their organizations should consistently drive toward a common storage architecture framework across their enterprise. They also need to take into account not only the wide range of current storage needs, but how the storage requirements of the organization might change over time. As such, data storage leaders must evaluate technologies from the perspective of how they will support future demand for storage. That’s not easy to do, considering how much and how quickly things change.

There are many data storage solutions available today, including cloud-based solutions and on-premises systems. Working with knowledgeable, independent consultants can help storage teams separate marketing from reality and assess which of these is best suited to meet the organization’s needs now and in the months and years to come. Part of the strategy includes estimating current and future costs of storage, and how options such as the cloud can have an impact on economics (cost per GB/TB is constantly decreasing, based on consumption, and requires no new hardware installations or upgrades).

One of the key developing trends in storage is automation. The ability to automate processes extends to storage management, and with the advancements in cloud services, artificial intelligence (AI), and other areas, organizations are presented with more opportunities than ever to automate management and add flexibility and scalability.

Another major decision is whether to move storage into the cloud—and whether it should be via private clouds, public clouds or a hybrid environment with both. Managers also need to decide when it makes sense to handle storage at the edge of the network rather than in the cloud. Edge processing and analytics will become critical to performance and business relevance as companies’ IoT initiatives continue to expand.

One of the most important factors, the data storage teams need to keep in mind when developing a storage strategy, is how to ensure the security of the systems and data. Data protection can be far more difficult when the environment is more complex, which is the case with IT infrastructures that include multiple cloud services and edge computing.

Safeguarding sensitive data such as personally identifiable customer information is one of the most business-critical priorities any organization has. For that reason, enterprises need to classify data, always know the location of the most highly sensitive data and who has access to the information, and deploy encryption technologies at every stage of the data handling process.

With the emergence of new regulations governing the security and privacy of data, such as the General Data Protection Regulation (GDPR) that took affect in May 2018, companies can be hit with significant fines if they are found to be non-compliant or suffer an information breach, without having taken the appropriate steps to prevent such an incident.

A good cyber security program will include comprehensive monitoring of cloud services, so the Security Operations Center (SOC) has visibility into cloud services and who is using them. By integrating various storage, monitoring, and visibility platforms, organizations can better leverage their IT investments, reduce risk, and reduce downtime.

Finally, when planning and executing a new storage strategy, don’t neglect to have the right skill sets in place. Effective data storage today requires having people who have a good grasp of the cloud, data architecture, software-defined storage, edge computing, and able to keep up with the future trends to adopt innovations that become available.

There’s also a need to work with experts in AI, machine learning, IoT, data visualization, and cyber security. With the right processes, technology, and skills in place, organizations can create a data storage strategy that will support the business for years to come.