Big Data continued to evolve and impact various aspects of business throughout 2015. It is assumed that the same will hold true in 2016 as well. Industry experts are of the opinion that Big Data will continue to be the market disruptor as machine data analytics will begin to emerge as a crucial player. Let us have a look at the top data trends that are expected to create an impact in 2016.
Emergence of new tools to facilitate DevOps
Machine data analytics is yet to reach its peak in the Big Data world. But with software becoming more and more crucial for driving business processes and business models, the advent of machine data analytics as a key player is just a matter of time.
As cloud continues to grow and expand its influence over businesses, organizations will be bound to look for new technologies that will help to enhance their business speed. This will also result in the need for innovative tools that will act as the collaborators between software developers and IT operations professionals.
The emergence and acceptance of DevOps approach by organizations will impact the need of new DevOps tools to cope with the changing times. 2016 is expected to be the year when DevOps will adopt machine data analytics services that function at cloud-scale in order to improve performance and deliver seamless results.
Escalation of investment in system intelligence
Organizations have been using Big Data to obtain actionable insights that help them in business decisions. With the improvement in technology data analytics is helping organizations to gain business insights at granular level in systems infrastructure, which is a new development in the business world.
In case of professionals dealing with security, analytics is developing better and faster intelligence pertaining to threat detection, system and user anomalies and breach alerts. This development is expected to have a profound impact on the way security leaders will think about the architecture of security systems in the future. It is also expected that security teams will collaborate with DevOps teams to increase the security of new application architectures through the use of embedded security capabilities.
Consideration of log management for application development
Log data has not been given much priority till now as far as application development is concerned. But the emergence of analytics has opened the possibilities of using it as a means to manage and collect insights from application, user or infrastructure logs in an effort to deal with the increasing complexities related to cloud and hybrid-cloud infrastructures.
It is assumed that the coming year will see the advent of vendors who will deal with the logs analytics space. This will enhance the awareness among organizations regarding the value of log management in relation to application development and IT operational success.
Advent of Extreme Architecture
It is a known fact that the improvement in the capacity and processing power of microprocessors have often resulted in software advancement. But with the emergence of cloud infrastructure things are not going to be the same as before.
The popularity of cloud infrastructure is expected to give rise to the need of new architectures that will be able to utilize the processing power existing in public or private cloud infrastructures. Such architectures are expected to be software based, possessing the capability to reduce traditional in-house data center constraints related to performance, preservation and management. Such extreme architectures are also expected to enhance the emphasis on application layer so that they can deliver the functionality required to address varied customer experiences.
Simplification of Big Data technologies
As Big Data continues to grow and become bigger and more effective, the market is experiencing the need to simplify Big Data technologies. It is not a far-fetched thought as the scope to simplify Big Data technologies exists at various levels, including the technical and consumption levels.
The coming year is expected to herald in the era of Big Data simplification. Hadoop is one of the main technologies related to Big Data. But the need to have simple and straightforward technologies related to Hadoop and other Big Data technologies has started to make its presence felt. The beginning is expected to comprise of initiatives like the reduction in the number of setting or profiles or the emergence of a single integrated developer experience. This trend is expected to bring in a new chapter in the Big Data history.
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