10 big data predictions that will soon change the world

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Although big data analytic is considered generally at its infancy, it is safe to say we are living in a world, where data is becoming a prized commodity, and its significance on a gradual rise. Infact, pundits and industry watchers have predicted that, the next 15-20 years promise to be an exciting time with data. They are already estimating that by 2020, every individual in the world will be creating at least seven megabytes (7 MB) of data per second.

One of the industry watchers and anylysts, who believe strongly in this preposition is Jacobs Edo, author of the best-selling book “Digital Transformation: Evolving a digitally enabled Nigerian Public Service” and a System Coordinator for the OPEC Fund for International Development since 2010.

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In a recent presentation titled “The Future of Big Data and Analytics”, he listed 10 big data predictions that would change the world. They are:

Big data analytics is the future of healthcare. According to Edo, big data in healthcare would not only profit every industry player, allowing for superior care and providing access to low-cost healthcare in the future, but would also most importantly benefit the patient by providing the right treatment, based on a sustainable pricing model. It will soon be possible to predict precisely how every segment of the healthcare industry would be impacted by big data, enabling us to fully comprehend how it should encourage desirable behaviours and minimise less desirable behaviours.

Big data processing moves to the edge. One way to handle the increasingly growing data generation and consumption challenge, especially those related to the Internet of Things (IoT) will be a gradual movement of big data processing activity to the network edge. With edge computing, much of the heavy big data lifting will be offloaded to network devices instead of pushing everything to the centre or multi-tenancy cloud platform for processing.

Data-as-a-Service (DaaS) is the new fuel for business success. He described Data as a Service (DaaS) is an information provision and distribution model in which data files (including text, images, sounds, and videos) are made available to customers over a network, typically the Internet. Increasingly, organisations are coming to terms with the value proposition of (big) data. This strategic understanding that a company’s data should be its greatest asset will soon become widespread. Technically, the initiative of data as a service involves the consolidation and reorganisation of existing enterprise data in one place, then making it available to serve new and existing digital exploration purposes.

Internet of Everything (IoE) wins a popularity contest. It is now common place in this age of digital transformation that object enchantment is another name for digitalisation. To make an object, process or anything smart today means adding a digital interface. Thereby transforming a dumb object into an intelligent edge device that can be further leveraged for computing power

Smart analytics, the future of business intelligence. In the coming years the maturity of smart analytics will be completed, with business intelligence and analytic reporting as we know it today going obsolete. Smart analytics will natively incorporate real-time automated data discovery, meta-data extraction, and artificial intelligence analysis enabled algorithms designed to spot real-time influencers, key drivers, relationship, and exception in data.

The age of algorithms. As the rise and performance of data-driven leadership and corporate strategy formulation increases, businesses and institutions will be challenged to acquire the most productivity and performance enhancing algorithms instead of software. The expectation will be for companies to continuously iterate their go-to-market strategies, though own data and algorithmic enabled options customisation.

The awakening of cloud 2.0. The cloud will continue to win and lead the way for on-going emerging technological convergence and innovation. Cloud 1.0 has provided an exciting pedestal and an extremely stable foundation for many businesses to build their cloud adoption strategies. The increasing rate of data production and consumption is already impacting existing cloud infrastructure providers, enterprises and existing cloud adopters, pushing them to use this enormous resource to evolve an innately data-driven intelligence infrastructure that improves significantly on agility, security and data analysis.

Personalised pricing is the future of competitive pricing. Dynamic pricing or flexible pricing isn’t new. Before the 19th century, customers haggled for discounts, and loyal patrons were often given a “friendly price.” Mass marketing introduced a little more science by using demographic research, and more recently big data and analytics, but lost the shopkeeper’s ability to negotiate with a customer directly. Prices now are mostly set according to market segment and supply-demand, not based on first-hand buyer knowledge.

The rise of data-driven strategy and leadership. Big data importance is on the rise as the attention of most industries are now laser-focused on it. Senior management and top executives across the globe are currently seeking expert guidance for big data analytics best practices and greater understanding of its role in strategic decision making. The increasing power afforded this group of managers by big data analytics results within their various organisations will have a significant effect on corporate strategy.

Privacy takes a new life. The amount of data that we are creating and, the volume of data to be generated in the future and their associated importance and use cases makes data privacy and security of most importance whether now or in the future. In most of the developed world, privacy is considered a fundamental human right, and it’s protected by law.

 

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