Data Science is the study of the flow of information from huge amounts of data present in an organization’s repository. Netflix’s Recommendation Engine, and Apple’s Siri—all of these are real-life applications of Data Science. In this article we will study about Data Science in detail and the best data science career available. So without any further delay let’s get started.


What is Data Science?

It is a detailed study of the flow of information from huge amounts of data present in an organization’s repository. It involves obtaining information from raw and unstructured data which is processed through analytical, programming, and business skills.

Data science

In a world that is increasingly becoming a digital space, organizations deal with structured and unstructured data every day. The technologies have enabled cost savings and smarter storage spaces to store critical data.

Importance of Data Science

Let us see some reasons which focus on the importance of Data Science.

  • It allows products to tell their story powerfully and engagingly.
  • The industries can analyze their challenges easily and can also address them effectively.
  • It helps organizations to build this connection with the clients.
  • The companies will be able to recognize their client in a more improved and enhanced way

Data Science Life cycle

The TDSP lifecycle has five major stages that are executed. The five stages are:

  • Business understanding
  • Data acquisition and understanding
  • Modeling
  • Deployment
  • Customer acceptance

How top industry use Data Science

IT organizations need to address their complex data environments in order to identify new value sources and optimize themselves, efficiently. The deciding factor for an organization is ‘what value they extract from their data repository using analytics and how well they present it’.


Google is by far the biggest company that is hiring trained Data Scientists. Since Google is mostly driven by Data Science, Artificial Intelligence, and Machine Learning these days, it offers one of the best salaries to its employees.


Amazon is a global e-commerce and cloud computing giant that is hiring Data Scientists. They need Data Scientists to find out the customer mindset and enhance the geographical reach of both e-commerce and cloud domains, among other business-driven goals.

How to learn Data Science

The main question is how to learn data science.
Online classes can be a great way to quickly learn about the good stuff, from technical skills like Python or SQL to basic data analysis and machine learning. That said, you may need to invest to get the real deal.
Below are mentioned some links through which you can learn data science

You need relevant coding skills to learn data science

Click on this link: Improve Coding Skills With Online courses

Data Science careers

Experts are needed in virtually every job sector—not just in technology. In fact, the five biggest tech companies—Google, Amazon, Apple, Microsoft, and Facebook—only employ one half of one percent of U.S. employees. However—in order to break into these high-paying, in-demand roles—an advanced education is generally required.

Here are few data science career options:

Business Intelligence (BI) Developer

A business intelligence developer is an engineer that’s in charge of developing and maintaining BI interfaces. It includes query tools, data visualization, and interactive dashboards. But, as we are speaking about business intelligence, we need to give a stricter explanation of this technological concept.

Skills: ETL, developing reports, OLAP, cubes, web intelligence, business objects design,
Tools: Tableau, dashboard tools, SQL, SSAS, SSIS, and SPSS Modeler.

Data Scientist

Data scientists are analytical experts who utilize their skills in technology to find trends and manage data. They use industrial knowledge, contextual understanding, skepticism of existing assumptions – to uncover solutions to business challenges.

Skills: Python, R, Scala, Apache Spark, Hadoop, machine learning, deep learning, and statistics.
Tools: Data Science Experience, Jupyter, and RStudio.

Data Engineer

Data Engineers are the data professionals who prepare the “big data” infrastructure to be analyzed by Data Scientists. They are software engineers who design, build, integrate data from various resources, and manage big data.

Skills: Hadoop, MapReduce, Hive, Pig, Data streaming, NoSQL, SQL, programming.
Tools: DashDB, MySQL, MongoDB, Cassandra

Data Analyst

Data Analysts are experienced data professionals in their organization who process data, provide reports, summarize and visualize data. They have a strong understanding of existing tools and methods to solve a problem.

Skills: Data Analysts need to have a baseline understanding of some core skills: statistics, data munging, data visualization, exploratory data analysis,
Tools: Microsoft Excel, SPSS, SPSS Modeler, SAS, SAS Miner, SQL, Microsoft Access, Tableau, SSAS.


Data science is an emerging field that is revolutionizing science and industries. Work across nearly all domains is becoming more data driven, affecting both the jobs that are available and the skills that are required. As more data and ways of analyzing them become available, more aspects of the economy, society, and daily life will become dependent on data. It is imperative that educators, administrators, and students begin today to consider how to best prepare for and keep pace with this data-driven era of tomorrow. Undergraduate teaching, in particular, offers a critical link in offering more data science exposure to students and expanding the supply of data science talent.