Big Data is transforming the way companies, governments and individuals do just about everything. It is such data that is allowing different entities to lower cost, increase revenue and have a respective competitive edge. When valid data is analyzed correctly, the more precise and valuable it will be, and so will the decisions deriving from them.

Big data analytics, digital information stored at high volume, velocity and variety, is the process of using software to identify trends, patterns, correlations or other useful insights for companies to enhance, transform and grow their business. Many experts predict that the future for Big Data is going to look even brighter than its recent past and there are good reasons for companies and individual Big Data job seekers to be excited about it:

Data volumes will continue to grow, so too will the number of Big Data Adopters. More data has been generated in the past two years than in the previous 5,000 years. In 2017, it’s estimated that more than this will be created in a single year and there will be even greater data growth in the future since handheld tech is still increasing exponentially. It’s no wonder companies around the world are rushing to adopt or grow their Big Data operations. Yet, research has found that less than 0.5 percent of that data is analysed for operational decision making and this means Potential with a capital ‘P’.

A Big Data analytic survey by Peer Research showed that, in 2015, only 11% of organisations within healthcare used data analytics and a similar situation existed within consumer retail, manufacturing and IT with 9%, 8% and 14% using analytics, respectively. As more companies jump on the Big Data bandwagon, data professionals could see themselves busy for a very long time. The main motivator for early adopters of Big Data are to improve profitability, align IT with business units and to focus on enhancing business outcomes (HPE, 2016).

A common misconception is that Big Data always requires enormous volumes of data and deep pockets. However, the volume of data and the budget aren’t as important as how data is interpreted. It’s pointless trying to decipher meaning from big data unless you’re willing to use the right tools. In fact, too much data can create information overload. Using KPI’s, volumes of data can be curtailed to answer questions and assist in decision making pertinent to a business.

Competitive advantage over non-users. According to the International Institute for Analytics, it’s estimated that Businesses utilizing Big Data could see up to $430 billion in productivity savings over non-users by 2020. Big data can identify areas where expenses can be reduced within an organization. Additionally, it assists in customizing products and services to their customers’ preferences, aiding in identifying new opportunities for revenue generation. In the MIT Sloan Management survey, 68 % of respondents agreed that analytics has helped their company innovate. Also, by applying big data techniques, organizations can identify cyber-attacks that would otherwise have gone unnoticed. It can also recognize social media, customer service, sales and marketing trends. This results in companies gaining competitive advantage.

Increasing Automation. The world is becoming ever more automated. No surprises there- it’s been happening for some time but with AI, Machine Learning, and the Internet of Things on the horizon, Big Data’s future is very exciting.

Many business owners think that Big Data is very complicated and are unaware that system tools for gathering and interpreting data are automated and designed to remove complexity. They’re tailor-made to business needs and require little human involvement.

Big data staffing shortages will grow. The skill gap which is opening in Big Data means, already high salaries are likely to increase further as demand for positions outstrips supply. The suggested range for Data Analysts at entry-level with 0 to 3 years of experience is €20,000 to €28,000 and for a Senior Analyst with 3 to 5 years of experience it would be €28,000 to €35,000. There are also higher level and better paid jobs- Data Scientists, Big Data Engineers, Data Visualization Developers, Development Ops Engineer just to name a few.

There are three major pluses for Big Data in the future. Firstly, there’s no limit to where Big Data Analytics can be applied and secondly, many industries are in the early stages of adoption. The final one is the emergence of new technologies which allow previously unimagined levels of automation that were once considered just science fiction. Add these up and the sky’s the limit for Big Data in this high-tech world of ours. Those organisations which embrace it will forge ahead, but those which are slow to do so will likely soon be has-beens.

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