The Ultimate Guide to Becoming a Data Scientist

By the time we reach 2020, we will be producing 50 times more data than we were producing in 2011. Considering this, it is obvious that we need more data scientists who can analyze and evaluate data and create insights from it to drive business growth.



Since the time “Data Scientist” was ranked as the hottest job of the 21st century by the Harvard Business Review, coupled with alluring paychecks, there has been a significant rise in demand for data-savvy enthusiasts in several businesses, nonprofit organizations, and public enterprises.  So if you are planning to become a data scientist, but wondering from where to begin, you’ve landed at the right place at the right time. Here is a complete guide to becoming a data scientist.

Important Steps You Should Follow to Become a Data Scientist

#1 Brush Up Your Skills in Mathematics and Statistics

You might know that statistics and probability tools are required in every predictive analysis, since mathematics and statistics are used in every corner of data science. Especially, machine learning and data mining are the fields where you cannot take even a single step without getting your hands into Mathematics and Statistics. Thus, it is wise to brush up your skills in these two fields if you are planning to become a data scientist.

#2 Learn to Love (Big) Data

Data science professionals have to deal with an enormous volume of structured and structured data on which computations can’t be performed using a single machine. Most of them use big data software like Spark, MapReduce, or Hadoop to achieve distributed processing.  There are many online data science programs out there that can really help you to learn about big data at your own pace.

#3 Learn How to Code

Until you learn the programming languages in which big data communicates, you won’t become a good data scientist. A well-organized chunk of data might be screaming out loud for its analysis; but you can’t decode it if you don’t know how to write code or a program script. Always remember that a good programmer might not be a good data scientist, but a good data scientist is definitely a great coder. 

#4 Must Have a Sound Knowledge of Databases

Given the voluminous amount of data generated virtually every minute, many businesses employ the latest database management software like Cassandra or MySQL to store and analyze data. Having a sound knowledge of the Database Management System (DBMS) will surely go a long way in your working as a data scientist.

#5 Work on Real Projects

Once you gain a deep knowledge of the theoretical aspects of data science, it’s time to put your knowledge into the practice.  Start looking for data science projects on the Internet and invest your time in strengthening your own forte. 

By following the steps discussed above, you’ll be on the right path to becoming a data scientist! With no further ado, you should start doing all this from today itself to get a competitive edge over others.

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