The IT industry is moving at an unprecedented pace. With effective data management no longer the sole domain of the IT department, there are many options and choices available for investment.
To assist, we’ve pulled together our top predictions for 2017. We hope you enjoy and please use the comment section below for any feedback.
Software Defined Storage
Next year (2017) will be a year where enterprises move software defined storage out of the lab and into production. Software defined storage has proved that it can reduce legacy hardware expenses while also delivering the performance and scalability needed for big data, digital repository, backup and other large digital workloads. With software defined storage, enterprises can avoid vendor lock-in, increase their use of the cloud and more rapidly deploy new applications and services, delivering them with significant competitive advantages in today’s digital economy. We also see an opportunity for enterprises to leverage the move to software defined storage to index and extract value from the data, beyond providing a less expensive scale out storage option.
The Shakeup of the Storage Industry
Over the past few years, we have seen an increased shakeup in the data management sector with industry goliaths either merging or being acquired (i.e. EMC buying Dell and Symantec selling Veritas to Carlyle Group). Yet the market waits for no one. As enterprises increasingly seek to deploy new technologies and more cloud services, point solution vendors will fall by the wayside in favor of providers that can deliver powerful data management platforms that simplify and automate the management of today’s ever growing, ever more complicated data environments.
The Talent Pool
In today’ tight labor market, companies are increasingly seeking to expand their ability to reach, recruit, motivate and retain top talent. In this environment, all enterprises will need to adopt radical talent acquisition and retention strategies that emphasize process without bureaucracy if they hope to not only secure and keep skilled and motivated employees, but also ensure that all these employees are 'rowing together' in full alignment with the enterprise’s business goals. With a new administration settling into office, U.S.-based companies will also need to be strategic in navigating around potential new policies in immigration to find the right talent.
In 2017, organizations will take ransomware more seriously and implement ways to rapidly identify compromised content and automate its recovery. Ransomware has proved to be one of the most effective ways to infiltrate an organization, and cyber criminals are increasingly becoming better at embedding viruses into innocent-looking email attachments. Organizations need to figure out how to classify, separate and wall off their data in order to reduce the risk of data being inappropriately accessed and permanently lost. Discussions need to take place at the board level about an organization's data recovery strategy and its intersection with its security and ransomware strategy in order to keep sensitive data out of the hands of the wrong people.
Cloud Cost Models
An increase in data center hybridization also increases the ebb and flow of data that moves between the cloud and on-premises; current egress models weren’t developed with this level of data transfer between a variety of locations in mind. As enterprises increasingly embrace hybrid infrastructure models, the current pricing models from cloud service providers for moving data back and forth between on-premises and the cloud is becoming unsustainable. In 2017, these pricing models will need to adjust, or existing cloud providers could see new competitors steal their market share.
Intelligent Data Management Is No Longer a Luxury, But a Necessity
Enterprises will rush to deploy intelligent data management technologies as it becomes increasingly clear that traditional data management solutions simply can’t handle their growing need for a platform that can manage the interaction between their various data lakes, transparently protect all their data and ensure compliance with new EU and other data governance regulations.
Only intelligent data management can automate access to, transfer between and the syncing of data between dozens of applications, databases and various other enterprise data lakes – automation that is needed if enterprises do not want their IT administration costs to skyrocket and their business processes to slow to a crawl. In addition, intelligent data management is required if enterprises hope to eliminate manual data protection jobs and operations, and instead make data protection transparent, continuous and automatic.
Finally, only intelligent data protection provides enterprises with the power and visibility they need to makes sure that all their data is governed in a manner that complies with new EU data privacy laws and a host of other government regulations. Given all these forces, 2017 will be the year when enterprises will be forced to finally wake up and realize that intelligent data management is not a luxury – it is a necessity.