In the coming year, Big Data technology will continue to be the Big thing for business. Experts estimate the amount of data some companies hold could be worth $8 trillion or more. Access to such a massive amount of data can be both a curse and a blessing. It can help reduce decision-making times on one hand; and on the other hand, it also increases the need to hire people to draw meaningful insights from this data.
To leverage Big Data, companies will have to overcome an enormous skill gap in the talent market. In fact, one LinkedIn report nominated ‘Data Scientist’ as 2015’s Job of the Year. We at Absolutdata feel ‘Data Scientist’ is actually the Job of the Century.
Big Data Analytics Trends for 2016
With 2016 around the corner, action is already being taken. Companies have started hunting for data scientists, and recruiters are scanning the market to fill the gap between demand and supply at a faster pace.
Both have to be very aware of the following trends:
- Finding the Right Resources with the Right Skill Set
A good Big Data scientist should possess strong mathematical and analytical skills along with equal proficiency in handling massive data sets. One must be able to crunch numbers, understand the math behind building models, and find useable insights. To communicate the data findings effectively, data scientists also need sound knowledge of the business domain and an understanding of customers and processes. Managers at all levels need knowledge, skills, and experience to effectively start a career in this industry.
- Training the Current Team with the Right Skill Set
Often, companies choose to use a combination of hiring, retraining, and outsourcing to fill the demand-supply gap. But getting new salaries approved, working with recruiters, and interviewing and onboarding candidates is a time-consuming process. Companies are training employees to use Big Data platforms so that they are able to analyze large, messy, unstructured data quickly. Therefore, Big Data is creating big value calls for reskilling and retraining employees so that they can make data-driven decisions. Companies leading the revolution already have an experiment-focused, numerate, data-literate workforce.
- Outsourcing Big Data Needs
A gigantic amount of valuable information can be generated from Big Data, but accessing this could be challenging. To be frank, it typically lies beyond the scope of routine business intelligence. Many companies today are partnering with third parties to create and execute Big Data analytics strategies. Integrating external experts into their own Big Data team may be the best way for companies to stay ahead in this quickly-evolving space.
- Unloading the Rote Work to the Machines
To save the monotony of manually reading and coding every piece of text – which requires a good amount of human work hours – companies should automate most of their routine processes. Algorithms, like robots in manufacturing, are doing the mindless, repetitive tasks of discerning subject matter, keywords, and sentiment. Predictive coding, as it’s called, frees employees to focus more on case strategy than on the tedium of analyzing every single PDF and email message to figure out if it’s relevant to a case. Due to automation, people are only integral to the first and last steps: selecting the metric with which they’re concerned and then interpreting the statistical correlations. The entire process makes businesspeople more efficient.
Big Data analytics will become a key basis of competition in 2016. It will underpin new waves of productivity, growth, innovation, and consumer surplus — as long as the right policies and enablers are in place.