How To Excel In Data Science Field?

With college semesters coming to end, many students are moving towards their career path. A lot of these students want to enter the field of data science, but, they don’t know how. In this article, we will discuss how part of this career lane.

However, before we dive in a little deeper, let’s clear any doubts that you may have about the demand in this field. Research by Forrester says that companies utilize only 12 percent of available data. Humongous amounts of data flow into organizations every data. This data comes from several sources such as digital media, social networking platforms, e-commerce websites, etc. But, most of this data is unstructured, hence, not utilized.

This is not to say that organizations don’t realize that they are not using most of this collected data. It is just that they don’t have enough talented people onboard for the job.

Apart from this, one fact that we all know is that we are in an employee’s market. If you know your basics, it won’t be hard to get a job in this field.

Now, let’s get to the nitty-gritty of this topic and see how you can excel in this field.

What It Contains?

To become a data science expert, college students are required to understand the following:

  • Considering the data that we are collecting Hadoop knowledge is necessary to quickly divert this data in the relevant directions. This technology can help you explore, filter, and sample data with ease.


  • Just like Hadoop, Apache Spark is another important technology that you should not skip at any cost. Using this tool, you can compute complex algorithms quickly. This platform offers convenience and flexibility to data science engineers.


  • If you are entering the field of data science, it is unlikely for any data scientists to not cross paths with machine learning, neural networks, and natural language processing. Gain a fair share of knowledge on these techniques and technologies.


  • Lastly, you should understand data and know how you can use PowerBI and other similar tools to visualize data. You should be able to use past and present interpretations of data to execute current processes effectively.


Note: Knowledge of these technologies should be achieved through some professional, preferably someone working in the industry, to gain a proper understanding.

How It Is Evolving?

Despite the recurring need of developers, we believe in the years to come machines will take over most of the tasks. This is not to say that machines will start working autonomously without human help but machines will execute most of our tasks. Hence, many of the jobs will go to waste and many more new jobs will be created.

Therefore, we urge students and aspiring candidates to focus on gaining specific expertise. Pick an area of interest and specialize in this area. Learn every tool, technology, and concept related to this domain to survive in this career for a very, very long time.

The Secret Ingredients

The secret ingredients that go into making a good data scientist are constantly learning and knowing what the user wants.

Firstly, step away from your computer and analyze how your customers interact with your products. Understanding user interaction helps in building products and services that will bring value to your users.

Secondly, we have already discussed that the market is evolving. If you are not learning your way up, you may end up losing everything. The techniques, processes, and procedures that are relevant today may not hold as much value after even 5 years. Hence, from the starting adopt a habit of learning new concepts and getting acquainted with upcoming technologies.