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The top three data storage trends of the new IT era

By Knowledge Sharing, Trends

In the 2020s, we are seeing the new IT era of hybrid and multi-cloud data fabrics shape new challenges and opportunities for data storage and management. Data storage is evolving to accommodate an ever-higher quantity and quality of big data. Data management is being made more intelligent as it is augmented with AI and ML techniques. And cloud-based predictive analytics are going beyond the general AI hype to create significant value.

Let’s explore what’s driving these trends and how they are interrelated.

Bigger big data and higher data quality

Total global data will grow from 33 Zettabytes in 2018 to 175 Zettabytes by 2025 – Data Age 2025 The Digitalization of the World by IDC

Have you stopped to consider how huge “big data” is getting? This means that there will be increasingly more data to store. At the same time, the new IT era is challenging organizations to be more data-driven, and this means storing and analyzing more data. But it also means ensuring high data quality. This is important considering that poor data quality has been shown to cost organizations around $15 million per year by Gartner’s Data Quality Market Survey.

Another example of the increasing quantity of data is that the DNA sequencing industry is forecast to sequence 2 billion genomes by 2025, which is around 200 exabytes of unstructured data, according to ”The Evolution from Data Backup to Data Intelligence”, a survey by ESG. Both the capacity to store more data and the capability to maintain higher data quality could pose a risk of increasing operating costs for organizations. But you can rise to the challenge and do more with less by employing more intelligent data management.

Intelligent data management and augmented data management

The ESG survey cited above and on TechTarget also found that IT professionals have a wide variety of different definitions of what the term data management means but they are in agreement that it is increasingly important. Some defined it as optimizing data storage and access while others said it meant implementing compliance and privacy processes or data classification. 

“Intelligent data management” was suggested by the author of the ESG study, Christophe Bertrand, as a term to show what modern data management technology can do now. In another article on TechTarget, author Stacey Peterson notes that the increasing use of all-flash arrays and hybrid and hyper-converged infrastructure are key drivers of more intelligent data storage.

So, what does intelligent data management mean to you? Let’s look at a related term, augmented data management, to give you a better idea. Gartner ranked augmented data management as one of the top 10 data and analytics trends for 2020 and defined it as using ML and AI techniques to optimize and improve operations. To give you an example of how these groundbreaking technologies can be applied to create business value in data storage and management, we’ll turn to a related trend, cloud-based predictive analytics.

Cloud-based predictive analytics

59% of global enterprises use advanced and predictive analytics – MicroStrategy’s 2020 Global State of Enterprise Analytics Report.

More and more companies are employing predictive analytics and the latest AI and ML technologies are increasingly powered by the cloud. As a result, the percentages of analytics platforms that are based in the cloud increased from 39% in 2018 to 47% in 2019 and is expected to continue growing, according to the MicroStrategy report cited above and on Forbes. Advances in cloud-based predictive analytics open the door to increasing data quality and obtaining more valuable insights to power more data-driven organizations.

But that’s not all. In “Cloud-Based Predictive Analytics Becoming a Critical Source of Vendor Differentiation in Enterprise Storage”, IDC Research Vice President Eric Burgener highlights “the use of AI and machine learning to drive autonomous operations” as one of three key features that set cloud-based predictive analytics apart from traditional remote monitoring. Such autonomous operations are the key to self-healing, storage optimization and future utilization predictions, which all have the potential to create significant business value.

Master the new IT era trends with the right tool

Given the latest trends, it’s now more important than ever to prepare your business to store more and better data efficiently while managing this data intelligently. With autonomous operations powered by cloud-based predictive analytics, you can insulate your workloads from downtime and data loss, save some serious money on storage costs and stay on top of future needs. 

This is exactly what we aim to help you do at STORViX. Contact us to learn how AiRE IntelligentFiler, our next-generation unified data platform, can help you leverage self-healing, cut storage costs in half and intelligently manage your data across hybrid and multi-cloud data fabrics to match your future needs.