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Many people ask if it’s possible to increase their earnings by moving into data analytics. The answer, clear and concise, is “YES”! But, there are some requirements one needs to meet for that.
Data analytics is today what computer was when it first came around in the 1960’s and 70’s. Network, as a newfound tool, attracted the attention of engineers and scientists across all fields with the new use of the machine being discovered almost every day due to its ability to fast and error-free calculation which later updated to storing of information and even receiving and transmitting them very fast. This led to widespread applications of the computer during that time which has only increased since then. Data analytics is in a similar situation today.
Also Article : Career Opportunity in Data Analytics

The sudden interest in Data Analytics

Data analytics jobs have emerged as a significant field of attention in recent years due to the advancement of computational and mathematical models by companies such as Google, Amazon, Microsoft, etc. Add into it the near-universal connectivity and access provided by technologies such as GPS, cloud and smartphones in modern time, and we get a giant network of interconnected devices continually generating data which can be used by the organisations for their benefits. The analysis and of this data and concluding from it falls under data analyst responsibilities which is in significant demand right now as companies are willing to offer much pay package and amenities to data analysts.
However, people often tend to forget that the salary offered to them by companies comes from the profits earned by it from the end user side. So, unless a working professional can add a sort of value to the company, he/she cannot expect an excellent salary even from the data analyst job.
Some of the factors required from a person for value creation are –

  • Mindset
  • Knowledge
  • Skills

A data analyst career needs an analytic mindset just like a career in computers required a computing mindset earlier. All of the students and professors of data analytics must ponder over the points mentioned below –

  1. All individuals related to the field of data analytics must be able to make sense out of a sense of numbers which seem unconnected at first glance. They must possess an eye for patterns and the ability to connect those patterns with the information available to them.
  2. The knowledge of analytics has evolved a lot over the years in the form of optimisation models, machine learning, statistical models, pattern recognition techniques, artificial intelligence, etc. Such a dynamic evolution of the field demands the professionals to be at their toes always. Any person looking to thrive must undergo proper data analytics training to survive the competition in the area.
  3. Just as the advent of the computer prompted professionals to learn programming and coding in the 60’s, data analytics requires the learning of analytical tools and languages such as Java, R, C++, etc. An analytics certification goes a long way in establishing the qualification of the person in the field.

So, the people who ask whether it is possible to double their salary by turning into data analytics must ask themselves whether they possess the mindset required for it or not first. It’s true that a data analyst salary is excellent compared to another field in today’s time, but one needs to do a lot of hard work and must possess the ability to impart value to his/her organisation to achieve that. Getting a top rank in analytics doesn’t guarantee success. Instead one must possess the ability to apply the knowledge for the company to make it.
Related Article : Data Analytics Popular Algorithms Explained

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Imarticus Learning is India’s leading professional education institute that offers training in Financial Services, Data Analytics & Technology. We’ve successfully transformed careers of over 35,000+ individuals globally through our Certification, Prodegree, and Post Graduate programs offered in association with leading and renowned global organisations in the Financial Services, Data Analytics & Technology domain.
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