What's In Store For Data Management In 2017
The year 2016 has seen the global and Indian enterprise storage market rapidly picking up pace, primarily due to the increase in generation of data due to digitization. This period of transformation holds plenty of promise as it is likely to offer a number of opportunities for data management firms in the coming years. The external storage market in India hit $330 million in 2016 and is expected to keep growing at a CAGR of 6.8% until 2020.
Mark Bregman, Chief Technology Officer – NetApp expects to see continuity in the shift towards adoption of cloud solutions in 2017, not just for its cost efficiencies but also to reach out to new markets and increase productivity.
Here are the top transformative technology trends and developments that will define the data management space in 2017, both globally and in India.
Data Is the New Currency
The explosion of data in today’s digital economy has resulted in a fundamental shift from using data to run the business to recognizing that data is the business. With data so valuable to success, it has become the new currency of the digital age and has the potential to reshape every facet of the enterprise from business models to technology and user expectations. We’ve seen this in the emergence of companies like Uber and Airbnb, which are built around the control of a network of resources. To make things even more interesting, we continue to see new types of data that enterprises didn’t used to think about collecting. For example, whereas we used to store and share only critical transactional data, we now store mass amounts of ancillary data surrounding transactions for deep analysis. This can include click stream data and even data about weather and other external factors that provide market insight.
New Models Take Hold
The focus on data requires a universe of services that can work together to solve critical problems of all types. This will require the support of platforms and an ecosystem of providers and developers that enables them. In this context, the platform model carries intrinsic value in its ability to integrate and simplify the delivery of services. A good example of this is Amazon Web Services, which continues to evolve into a richer and richer set of services all the time. Platforms create a virtuous cycle as does a good flea market: people go there to buy because that’s where people are selling; sellers go there to sell because that’s where the buyers are. As access to critical skills is becoming more challenging, broad-based platforms allow a more fluid flow of talent. People with specialized skills are attracted to projects they find interesting and the ubiquity of common platforms and tools makes it easier to engage their interests.
The Cloud as Catalyst and Accelerator
More organizations have been deploying cloud technologies to support their data requirements. The ready availability of cloud-based services provides easy access to the infrastructure needed to support innovation because it has dramatically lowered barriers to entry: with a credit card and an AWS account, new projects can be set up in a day and operate on a pay-as-you-go basis. An example of this is Cloud Sync Service, which was built by six engineers in six months with no capex infrastructure. New usage-based consumption models, based on Platform as a Service combined with new scale, compliance and data protection offerings, are making cloud infrastructure more essential for businesses of all sizes.
New Technologies Become Standard
All of these business drivers will ultimately lead to the dominance of new technologies, particularly in the form of new application paradigms. We’ve seen this emerge in the form of today’s DevOps movement where compositional programming based on micro services and mashups, open source and containerization have taken hold. Currently, these are considered niche solutions, but as the value of data becomes more critical to business and the pace of innovation becomes an even more crucial competitive weapon, they will quickly move into the mainstream. As that happens, these technologies will further reduce friction in the integration of businesses and the movement of talent. Historic parallels include the emergence of Ethernet as a networking standard and Linux as a standard operating system.
A Wider Dynamic Range of Storage and Data Management Technologies Evolves
As IT architectures evolve to accommodate new cloud infrastructure and new applications, a wider dynamic range of storage technologies will also emerge. We’ve witnessed how flash storage has quickly gained in popularity offering incredible efficiency and performance. Likewise, hyper-converged infrastructure (HCI) is one of the new IT architectures that addresses the critical demand for simplicity and reduces the need for administrative resources to manage storage.
While the first wave of HCI solutions have done that well, they have not addressed additional requirements for flexibility and scalability. Building web scale infrastructure will call for the flexibility to adapt the ratio of compute to storage according to the need, enable the upgrade of compute and storage separately, and scale easily and cost effectively.
Expect the next wave of HCI solutions to leverage what we’ve learned from converged infrastructure to deliver web scale converged infrastructure that meets these requirements. We also see the build out of higher bandwidth networks to manage the movement of large volumes of data. On the horizon, storage technologies such as archive class storage and massive persistent memory are next in line for adoption. The rapid development of easy and accessible data management services will allow for easier deployment of these emerging technologies.
Consumerization of IT Persists
Perhaps most profound is the change in user expectations of iPhone-like simplicity and self-management and the integration of applications and services. These expectations are affecting development across all technologies in storage and data management. User experiences with mobile app simplicity in a wide variety of forms has raised expectations for the usability and simplicity of data management software. And from a business standpoint, companies are demanding this simplicity because it will enable them to use less expensive resources to manage their data while giving them greater access and use of their data as a critical business asset.
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