The Analytics & Big Data sector has been consistently growing in the last five years despite an increasingly volatile and undetermined global outlook. Despite of this outlook the analytics and Big Data market is expected to grow in the overall IT markets. Here we assess the global scenario reasons for the growth, individual returns in terms of salary and what impact Analytics and Big Data has in todays economy.

Impact on businesses
Analytics & Big Data have revolutionized the way business is done around the world. All companies, small sized or fortune 500, rely on data and analytics to make critical business decisions. From understanding consumer behavior to predicting market trends, even right down to product features, many moves are driven by analytics and data in companies across the world.

In today’s global world Big Data and Analytics is used in Entertainment, Education, Transportation, Government, Defense, Retail, Health care, Finance.

For Example, Amazon is one of the leading consumer companies in the world using analytics and Big Data to configure their products, services and delivery. Amazon uses analytics to suggest products on their customer homepage based on the customer’s previous purchase history and browsing habits. They analyse the customer mindset based on the sites frequently visited and the products purchased from other sites.

Twitter uses analytics to fill your news feed with updates from people you interact with the most. Flipkart and Snapdeal use Predictive Analytics. The Postal Service invests in gathering and analyzing data to improve last mile delivery operations

Hiring trends
Earlier people used to be specialized in just one tool or domain but not anymore. Just getting a Master’s degree or a MBA on a resume does no longer impress hiring companies.  Current day Companies are investing in employees who know how to use the entire tool set of analytics & Big Data. This year people who know R and Python command a premium. Companies are looking for Data Scientists. They want people who have the business knowledge and understanding of analytics. The person would need to know the market analysis and business knowledge of similar industries to get that job.

R and Python is the front-runner in the analytics race. If the skill set is more diverse and business knowledge oriented the more the person earns.

Strategists and Analysts skilled in both Big Data and Data Science are being snapped up at the highest salaries. Cash-strapped startups spend money on their star analysts but when it comes to tools, they prefer to use open-source ones like R.

Analysts can expect a steep increase in their salaries once they cross the 5-year mark.

Big Data analysts are on a better earning foothold. Big Data professionals earn more than data scientists, but at the same time if they are combined together and know how to work with both they would get a larger payout – Data scientist + Big Data Analyst.

Earnings and skill requirement as per Companies Size
Startup companies and mid-size companies need people who know R and they are willing to pay top dollar for it. R is in great demand across the board. But, if a person wants to join a large company, they would need to add SAS to their skills. This is due to the fact that larger companies can afford to pay for proprietary software’s like SAS which may not be available with smaller companies. The biggest jump in salaries is seen after the 5 year period, where analysts can expect up to a 70% raise with an average pay.

Guidelines for Anyone Considering a Career in Big Data Analytics
Data scientist is person with an analytical mindset. Data analysts have an inquisitive mind and enjoy quiz and solving complex puzzles. They also spend time on analyzing numbers, inspecting huge financial data to see if they can perceive any meaningful patterns or tell any discrepancies.

Pursue College Degree or enroll in Institutes offering Big Data Programs
After self-assessment one can analyse if they want to go to college get a degree in data science, or if doing an intensive certification course is more beneficial. The person can do a research to figure out which universities or institutes offer the courses or programs that suit their profile.

Familiarizing oneself with the data analytics landscape
Analytics comprises of various techniques and tools that can be utilized in different variations for the purpose of diversity in business or healthcare management. The person wishing to pursue data analytics must analyse the intended work ‘domain’ in order to decide the kind of courses they want to take. Keep in mind that some software skills are in greater demand in some professional sectors than others.

In-Demand Data Analytics Skills
While data analytics skills are in great demand these days, some skills are more in demand than others. A person’s hands-on experience with different kinds of software will help command better salaries than expertise in just one.

Big Data
Popular Big Data-specific skills include statistics, programming, and mathematical modelling. A combined knowledge of R and Python, can equip the person with these skills.

Sometimes referred to as ‘a hyperactive version of excel’, R is used by organizations as varied as Facebook, Google and leading news agencies. It’s used to sift through large data sets, that it can then easily ‘manipulate’ using modelling techniques and powerful data visualization tools.

Python is a versatile, open-source programming language and framework. It is fairly easy to learn and pick up Python’s framework. It can be used to create web apps and also perform analytics Python is leading as one of the most popular coding language in the world. It was developed by Guido Van Rossum in the mid-90s.

Like Big Data, Hadoop is increasingly being referenced in job advertisements. Due to large capacity Hadoop computes with Big Data on a large scale. Hadoop’s growing demand and appeal shows no sign of decreasing in the coming years.

Following are the industries driving the growing demand for data science skills. This growing trend is expected to keep increasing in the coming years.

  • Scientific and Health care Services
  • Technical Services
  • Information Technologies
  • Manufacturing
  • Finance and Insurance
  • Retail
  • Government