Predictions of Big Data in 2017
Big data has truly evolved very big. Big data has become a very important of company’s business strategies and IT infrastructure. It is no more a buzzword now. The process of storing, analyzing and storing big data is changing the entire way of doing business. Industry has already crossed the half way of the path of biggest transformation in computing which will take place in the coming years.
With the improvements in technology, patterns are developed which indicate the current as well as future performance. Organizations now rely on such patterns. They are quite helpful for measuring the performance. Nonetheless, the advancements that are achieved in Big Data deployments are enabling organizations to discover where exactly they can target and achieve big accomplishments in the near future. Not to ignore the constantly changing market, business and technical scenario, it is challenging to segregate between what is propaganda and what is a reality. Don’t forget to take into consideration the noisy marketplace. However, with such things happening around the corner, Big Data will grow big and big in the coming years. Let’s find out some top predictions of Big Data in 2017.
A converged approach
Operational and analytic systems should be kept distinct in business applications. This practice is deployed since years and is regarded the best practice till date. Operational processing is prevented from being disrupted by analytic workload. Gartner coined the term “HTAP” Hybrid Transaction/Analytical Processing in 2014 describing an all new creation of in-memory data platforms. Well this new creation can perform both OLAP (Online analytical processing) and OLTP (Online Transaction Processing), without duplicating the data.
Something that was already happening in the marketplace was given a new name by Gartner. Be ready for converged approaches as these approaches will become more mainstream because organizations will reap the benefits of combining analytics with production workloads. This is done because of changing customer preferences, changing business scenarios. This helps organizations to meet the changing expectations of consumers and maintain the long term relation with consumers. Moreover, it speeds up the call to action process for companies and eliminates the expectancy between the tangible impact on business and the analytical processes.
Distributed Data in action
There have been a lot of changes in opinions between distributed and centralized model of workloads. But, if we talk about Big Data, the solutions were deployed on centralized model platform reducing data replication, streamlined management as well as supporting multiple applications including an overall customer analysis.
With the advent of 2017 and people believing the charm of 2017 will play very well, multinational companies will shift to processing Big Data in a distributed fashion to meet the challenges of handling various data centers, devices etc. in various locations. Booming Internet of Things (IoT) connected devices, superfast networks will further encourage the deployment and development of distributed processing structures. This deployment will surely benefit multiple data sources delivering data to network instantaneously.
New designs have been developed in storage products computer, consumer and enterprise markets with the advancements made in Flash memory. As consumers demand more for flash, costs will go down certainly and this in turn will encourage deployment of flash in Big Data. Nonetheless, flash and disk storage will be used by optimal solution to support both dense and fast configurations. Eventually, companies will no longer be in a dilemma to choose between one and the other. This is because this year, software which is new generation software- based which will help in proliferating multi-temperature solutions and aces to both will be guaranteed.
Focus on established solutions
2017 is the year of value addition. In 2017, market and organizations will focus on established solutions rather than shiny objects that don’t deliver any fundamental business value. Open source innovations which are community driven will still continue but organizations will realize the and deploy products that have a concrete business impact unlike other Big data technologies that just promise a new way of working but no impact is noticed.
Quality is everything
Organizations and investors will no longer prefer Big Data technology providers which often change their process models and still are not able to land on one model that can deliver valuable business. This year the focus will be on working safely with providers that have a guaranteed business model and technological innovations that will deliver enhanced operational proficiencies and more valuable business upshots.
With the technological advancements, an organization’s competitive advantage depends on the ability of leveraging data to gain business results. However, to actually implement this is not that easy. Enterprises having admittance to converged data platform can have the benefit of multiplicity of data services and tools to be processed on a solitary platform, harnessing insights that too real time from streaming information. With this, real time views can be translated into their operations, products and customers.