A Simple Guide to Data Science

With advancements in technology, data science has become a rewarding career option globally. The sectors like Information technology, telecom, manufacturing, retail industry, etc., need a data analyst to collect massive data and record them. Before you pursue your career in data science, first understand what is data science, the skills required to become a data analyst, prospects, etc.

Before pegging down a career in data science, go through this simple guide.

What is Data Science?

 Data science is a multidisciplinary domain that works with a large amount of data to find the insights of big businesses with the help of statistics and analytics. The work of a data analyst is to use their mathematics and programming knowledge to organize businesses’ data. Moreover, data analysts provide solutions to business challenges.

What are the skills required to pursue a career in Data Science?

 Perfection in Mathematics and Statistics:

As a data scientist, you must have extraordinary skills in solving differential calculus, integral calculus, differential equations, algebra, statistics, and probability theory.

Knowledge of programming language in computer science:

If you want to continue in data science, you must be familiar with programming languages like Python, Java, Perl, C++, and R. You should have knowledge of database programming languages like NoSQL and SQL. Some additional skills will add value to your professions, like strong command of some business intelligence tools like Tableau. Skills in solving big data, algorithms, etc.

Career opportunities in Data Science

  1. Data Scientist

As a data scientist, you occupy diverse domains like mathematical and technical acumen to identify a pattern and trends and make a prediction based on that data. A data scientist has vast experience in Artificial Intelligence, machine learning, data engineering, and statistics.

  1. Data Engineer

As technology advances, the demand for data engineers has increased as large data collection has become a necessity. A data engineer helps maintain the data pipelines and builds APIs to support the data repositories.

  1. Data Architect

Data Architect works on base data to identify its quality and accessibility and do security checks. Data Architect primarily works for the organization and help in maintaining their data.

  1. Business Analyst

Business Analysts are in great demand as they work with businesses and management to identify the technical solutions for a business problem. They mainly help the businesses in planning their finance and offers unique marketing strategy.

What are the prospects of Data science?

 It helps the e-commerce business predict their profit, losses, sales, changes in buying decisions, review analysis, etc.

  • Banking and finance industry; for data analysis of transactions and fraud management.
  • In the medical field, like analyzing patients’ medical history, medicines supply, shortage, etc.

Know about the B.Tech in Computer Science and Engineering course.

Hope this quick guide of Data Science was helpful!