7 Skills That Data Scientists Need To Know Via Big Data Analytics Courses

February 18, 2019
Data Analytics

 

Data analytics is one of the most sought-after careers of today. Being a good data scientist involves developing a lot of skills essential to the job.

Here are a few skills you need to have on your resume if you want to become a good data scientist:

1.  Being capable of handling unstructured data

Unstructured data refers to any data that cannot be made to fit into any database tables. This data can include customer reviews, audio clips, blogs, posts, or even videos. Arranging such data into specific categories can be quite the daunting task. As a data scientist, you must be able to work with a lot of unstructured data. Some software that you need to know how to use for this purpose are NoSQL, Microsoft HDI insight, Polybase, Apache Hadoop, Presto etc. 

2.  Good knowledge of Mathematics and Statistics

A good understanding of statistics is essential for anyone looking to become a data scientist. You must be familiar with all kinds of statistical concepts such as distributions and tests. Also, making predictions requires that you familiadata r the basic operation of calculus and linear algebra.

3.  Using data to tell a story

It is always easier for clients to understand data analytics if it is presented in a visual format using graphs, charts etc. Therefore you must have the capability to visualize raw data in a form that the layman can understand.

4.  Programming Skills

As a data scientist, you will be working with a lot of software that will require you to enter the code manually. As such, you must have a good knowledge of programming languages such as R and Python, which are normally used in data analytics. You must be able to write, understand and correct any code no matter the circumstances.

5.  A Competitive Spirit

As a data scientist, you will have to work on your toes more often than not. Therefore, it is essential for you to have a competitive spirit that will help you thrive. Hackerearth and NMIMS are two of the platforms that conduct hackathons, seminars and other competitions where you can gain more knowledge and understand all the latest trends in data analytics.

6.  Working on Projects

You must take up some live projects so that you get some hands-on experience in the field. This is important since most companies are looking for data scientists who are experienced in the field.

7.  Academic Qualifications

Most companies prefer their data scientists to have done their master’s degrees in the fields of computer sciences, mathematics, statistics and physical science. If you’re interested in working with research companies, then it will be advantageous to have a PhD in the same subjects.

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