Technical Skills Required to become Data Scientist

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27 Sept 2022

Over the years, companies have come to realize the importance of historical data in their businesses or organization. Companies are starting to enjoy the availability of insight and predictive models done by data analysts and data scientists. Thus making data science the most desired, most sorted job, and highly paid job presently.

The path to becoming a successful data scientist is not easy as it may sound. Skills sets required to master your career in this field, you’re required to be an expert handling this set of tools and languages along with statistical computations.

Tools For Basic Programming

Data scientists require knowledge of programming languages to be able to manipulate the data and apply sets of algorithms to data and generate insight. Major languages that are used by data scientists:
Python
R Programming
SQL- (structured query language) is a programming language that can help you to carry out analytical functions and transform database structures.

Statistics

Having a strong understanding of statistics and mathematics gives you a base to your career and also ensure that you’re learning them thoroughly so that you can implement them in any real-life scenarios. You could earn a Bachelor’s degree, Master's degree, or Ph.D. in Computer science, Social sciences, and Statistics. The most common fields of study are Mathematics and Statistics, followed by Computer Science and Engineering.

Tools for Data Visualization

Being a data scientist would require you to work on data visualization to display the pictorial forms of charts and graphs that can be easy to understand. Tools being used are:
Tableau
Power BI
Matplottlib
Qlikview
D3.js

Big Data

As a Data Scientist, you will have to deal with large amounts of data. Because data is being generated every day. Big data querying is primarily used to capture, store, extract, process and analyze useful information from different data sets.

Hadoop Platform

An open-source platform used to store and process large sets of data that can extend from gigabytes to petabytes. Hadoop platform is used when the volume of data you have exceeds the memory of your system or you need to send data to different servers. Hadoop can also be used for data exploration, data filtration, data sampling, and summarization.