Top Storage Trends that Data-Driven Enterprises Should Watch in 2020
In 2019, open-ended digital innovation and transformation across multiple industries had a lot of organizational leaders suffering from “digital transformation fatigue.” Trends in Big Data, artificial intelligence, data analytics, and data storage have created a “change or die” environment, especially when organizations aren’t getting satisfactory results. An October 2018 McKinsey & Company report revealed that 70 percent of organizations underwent drastic leadership changes—leaders unable to keep up with the fast-paced digital transformation were replaced by digital and tech-savvy leaders.
With less than 30 percent of enterprises successfully implementing a digital transformation strategy, only half of them were able to report sustainable performance improvements. Considering that even in digital-savvy industries such as telecommunications, media, and high-tech manufacturing there is only a 26 percent success rate, it shouldn’t be shocking to know that more traditional industries like healthcare, infrastructure, and oil and gas fall between the 11 to 4 percent mark with digital transformation. What does all of this have to do with the three top storage trends to prepare for in 2020? Keep reading to find out the answer to that question.
“Big data is at the foundation of all of the megatrends that are happening today, from social to mobile to the cloud to gaming.” – Chris Lynch
1. The Utilization of Modern Data Protection
Many experts are beginning to say that data is more valuable than gold or petroleum. Some decades ago, oil companies were some of the most valuable enterprises. Based on an article published by The Economist, however, titans like Alphabet (Google’s parent company), Microsoft, Facebook, Apple, and Amazon are the five most valuable listed firms on the globe. With their profits continuing to surge, the tech giants racked up $25 billion in net profits in the first quarter of 2017 alone.
To put this all in perspective, in the United States, Google and Facebook account for nearly all revenue growth in the digital advertising space, while Amazon seizes approximately half of all dollars spent online. Data has made these companies the most powerful commercial entities since the Dutch East India Company (though still not nearly as valuable). As with any asset that fuels business decisions and capability, your data must be managed in a way that strengths your enterprise—the same way as it has strengthened the aforementioned tech giants.
Defining Modern Data Protection
Data protection is a broad term. With the number of data protection products on the market, it’s vital to establish a baseline for a modern-day data protection suite beyond the obvious backing up and restoring of data.
Traditionally, data protection merely involved the capability of backing up and restoring lost or corrupted data on primary data storage systems. It can also include protecting data-in-transit over IP data networks. However, modern data protection will exceed that by focusing on how one can leverage secondary storage datasets as a source of empowerment for their organizations. Backups, snapshots, and replicas will no longer be viewed as a liability but rather as a benefit. This means secondary datasets can be used for testing workloads, data analytics, and software development and information-technology operations (better known as DevOps).
Most modern data protection products fall into one of three categories:
- Devices. All-in-one devices that incorporate storage and software needed for data protection.
- Software Only Solutions. Incorporate traditional applications; software-only solutions may also be installed in Infrastructure as a Service (IaaS) solutions.
- Software as a Service (SaaS). A cloud-based backup; with SaaS solutions, the provider manages the infrastructure.
Metadata, Data Deduplication, Disaster Recovery: Foundations of Modern Data Protection Platforms
Metadata is an indispensable enabler when it comes to leveraging the amount and relevance of data. Mining metadata allows companies to gain the ability of near real-time analysis of the location of data, as well as knowing who can access the data. With the most advanced systems, metadata enables organizations to index data distributed across the globe.
Data deduplication (dedupe) is one of the most crucial characteristics of any modern data protection program. Disaster recovery replication is powered by dedupe and facilitates leveraging public cloud storage for data tiering and archiving. Also, dedupe provides the foundation for data mobility for advanced data management capabilities such as data mobility.
Advancements in dedupe, as well as the economics of public cloud, has allowed leveraging backup products to power replication for disaster recovery to become more popular. Traditional disaster recovery designs replicate data from a tier 1 storage array located in the production data center to a tier 1 storage array located in a DR facility.
2. Increasing Storage Automation and Self-Service
Over recent years, the world has become very excited about Big Data and advanced analytics, and not merely because the data is big but also due to the big potential. When it comes to data management, automated data management is where the proverbial rubber meets the road when it comes to the future of IT.
The incoming data torrent, coupled with an eagerness to extract non-intuitive truths from all that data and the government’s desire to guarantee the privacy of users who generate the data, means problems in the not-too-distant future. The “zettabyte (ZB) apocalypse” is fast approaching; too much data, too much storage, too many storage services, and not enough human administrators to handle it all.
The International Data Corporation (IDC) has predicted that more than 160 ZB of new data will have been produced by 2025—that is only five years away, and the count down is ticking. According to Microsoft Azure, only 1.5 ZB worth of disk and non-volatile RAM storage was being manufactured on an annual basis (back in 2017). There is no telling where the industry is at now, but it’s simple to understand that the volume of data accumulating can’t be hosted with the equipment the industry has available at present. Fortunately, shortages will be managed by reduction and compression technologies.
Most IT professionals already know that the cost of any data storage solution doesn’t merely include the initial purchase cost, but also includes the total costs that come with support and human resources required to maintain such systems. This will propel the need for storage automation and self-service in 2020.
3. Incorporating Artificial Intelligence (AI)
AI is the next step toward structured data analytics. Storage is becoming progressively more intelligent as analytics capabilities are increasingly consolidated with arrays and other components of the storage layer. AI, ML, and predictive storage analytics are coming together to optimize and enhance storage infrastructures, allowing users to proactively address issues. Behind the drive for more intelligent storage is the adoption of hyper-configured infrastructure (HCI) and all-flash arrays (AFAs), as well as growing demand for real-time data on storage performance and capacity.
Last year’s Hadoop platform teams will be this year’s AI and analytics teams. Before you know it, an abundance of methods to obtain insights on data will have emerged. Statistical models have focalized with computer science to become AI, ML, DL. This translates to data, analytics, and AI teams collaborating to obtain benefit from the same data. This will be achieved by creating the correct data stack, computes, and storage silos used on-premise, in the cloud, or in both.
In 2020, this will not only become the norm but you will see more companies building devoted teams around this sort of data stack.
Storage in 2020 is no longer an exclusive slice of data center technology stack that can be intelligently managed or analyzed in an isolated environment. In order to view bigger slices of the data stack, one must employ a more sophisticated analytical approach over Big Data. Storage vendors assemble enormous amounts of data from customers while applying predictive modeling, analytical queries, and data mining to aggregated data sets to anticipate future trends. In addition to that, they’re providing the resulting analysis back to their customers, helping them reduce overhead, plan infrastructure, and proactively deal with issues before they present themselves.
AI and ML have been combined in predictive storage analytics, to continuously develop data analysis and data collection tools. What you get as a result is a self-healing storage infrastructure that automatically identifies and resolves issues, offers you improved capacity management, increased productivity, performance, application availability, and reduced downtime.
Storage Must Be Up to Par in Performance, Availability, and Reliability for AI
In a number of our articles, we’ve covered the importance of storage requirements for AI. In 2020, as AI becomes a more integral part of data analytics, we’ll see quad-level cell (QLC) and triple-level cell (TLC) technology complementing each other. Multi-level cell memory offers a number of benefits, such as its lower cost per unit of storage being one of the greatest benefits of them all. You can expect to see more QLC devices hitting the market in 2020, with some of them reaching a capacity of 32 TB and above.
Any data store supporting read-intensive applications can us QLC NAND (quad-level cell NAND) flash memory. It can be used for analytical applications that support AI, ML, and DL. The data in these situations is usually written once prior to being used for analytics that requires fast access to storage with huge volumes of data.
RAID.Inc is an industry leader in providing organizations custom high-performance storage solutions that deal with the end-to-end data management difficulties of every market. We offer the best in high-performance storage solutions such as Pangea, Xanadu, and Ability. Additionally, we layout, design, develop, execute and support these best high-performance storage solutions based on your budget, infrastructure, and needs.
There is a reason why leading national labs, research facilities, academic institutions, government agencies, and enterprises trust RAID Inc. with their data. If you would like to learn more about the latest trends shaping up in 2020, have further questions, or would like to talk to one of our experts about upgrading your data solutions, contact us today!
