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What is Data Science & How to become a Data Scientist?

We are into an era of big data, and as we moved forward the need for higher storage also grew higher. Until the previous decade, this storage concern was among the most important among the industries and multinational corporations. As time passed, the problem was solved and we moved to another concern of how the data can be processed. This is where Data Science placed the role of a secret ingredient. Data Science is the prospect and the future now, so it’s very significant to understand about Data Science and how that can add value to our lives.



What is Data Science?





Data Science is an amalgamation of various principles, tools, algorithm and structures with the main motive of bringing to light the unknown patterns or connections in raw data, so that it can be used by companies in business for their benefit and hence they find conclusions. The raw data used can be from many sources and can be present in any of the extensions.


Why Data Science?

Data Science is a decision making science of analysis and to discover patterns and make analysis through predictions. Data Science helps you in:


  1. Detecting the root cause of the problem and hence finding the solutions


  1. Explaining the data study

  2. Modelling the various algorithms and structures

  3. Communicating the data through various methods like traversal, graph, charts etc.


Data science is currently in application in many fields. Among them, the major is Airline Industry. Taking the help of Data Science, airlines are easing their operations in the following ways:


1. It helps in planning of routes, and even deciding whether to schedule direct flights or connecting flights for that particular destination


2. It helps determining the cost of travel and decide the flight fare accordingly


3. It helps in offering the customers a personalized experience, keeping in mind their previous bookings.





Essentials of Data Science


There are many computing concepts that should be known to us before we start doing data science.


1. Machine Learning

Machine Learning is said to be the brain of data science. People who study Data Science are known as Data Scientists and they should have a solid point on Machine Learning


2. Programming

There is an intermediate level of programming required to conclude and run any data science hands-on project. R and Python are among the most used programming languages for data science. Python is used widely because of it’s easy grasp and is common among the various data science projects.


3. Database

A Data Scientist should even have a good hand on Databases. He should know how to extract and edit data. Managing databases is very necessary in Data Science to get a correct output.


4. Statistics

If Machine Learning is the brain of data science, then Statistics is the backbone of data science. More intelligent results can be concluded with a good statistical study.


Role of a Data Scientist





The work of the data scientist, when he works for a business is to analyze the situations and provide meaningful insights. In another way, a data scientist provides solution of a business issue through a series of steps including:


  1. Understanding the problem by a asking critical and high order thinking questions


  1. Using multiple sources to gather data- enterprise data, public data, employee data etc


  1. Convert the data that is in raw format to the data in a presentable format to understand the situation better


  1. Insert the data into an algorithm model- Statistical Model or ML Model


  1. Obtaining the conclusions to be presented with meaningful observations to the needful people.



Applications of Data Science

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1. Data Science as a Career


Data Science field is growing nowadays with much torque. There is an increasing demand and it’s going to increase exponentially. As per a 2019 Report by Glassdoor, Data Scientist was the number one job in United States. Some statistics have given a prediction that the field of data science is going to create 11.5 million job vaccancies by the year 2026.

An average salary of a data scientist ranges from 9 lakh to 11 lakh per annum in India.


2. Healthcare

The medical associations are taking the help of data science to develop advanced equipment. This will help in curing dangerous diseases and can prove to be a life saver.


3. Fraud Detection in Credit Cards


It’s essential that master or credit cards organizations can distinguish false Visa exchanges with the goal that clients don’t need to pay for goods that they didn’t buy. These issues are to be handledusing Data Science, alongside Machine Learning, can’t be exaggerated. This venture plans to represent the displaying of an informational collection utilizing AI with Credit Card Fraud Detection. The imbalanced dataset issue happens in light of the fact that the quantity of real exchanges is a lot higher than the false ones though applying the correct component designing is significant as the highlights got from the ventures are restricted, and applying highlight building strategies and changing the dataset is pivotal.



How do top industry players use Data Science?

In this section of the ‘What is Data Science?’ blog, we will look at how top industry players like Google, Amazon, and Visa are using Data Science. IT organizations need to address their complex and expanding data environments in order to identify new value sources, exploit opportunities, and grow or optimize themselves, efficiently. Here, the deciding factor for an organization is ‘what value they extract from their data repository using analytics and how well they present it’. Below, we list some of the biggest and best companies that are hiring Data Scientists at top-notch salaries.


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


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


An online financial gateway for most companies, Visa does transactions worth hundreds and millions in a single day. Due to this, the need for Data Scientists is huge at Visa to generate more revenue, check fraudulent transactions, and customize products and services as per customer requirements, etc.

Data Science Life Cycle

For a better understanding of ‘What is Data Science?’, let’s explore its life cycle. Suppose, Mr. X is the owner of a retail store and his goal is to improve the sales of his store by identifying the drivers of sales. To accomplish the goal, he needs to answer the following questions:

  • Which are the most profitable products in the store?

  • How are the in-store promotions working?

  • Are the product placements effectively deployed?

His primary aim is to answer these questions which would surely influence the outcome of the project. Hence, he appoints you as a Data Scientist. Let’s solve this problem using the Data Science life cycle.



What is a Data Scientist?


Data Scientists are IT professionals whose main role in an organization is to perform data wrangling on a large volume of data—structured and unstructured—after gathering and analyzing it. They need this voluminous data for multiple reasons, including building hypotheses, analyzing market and customer patterns, and making inferences.

Their role requires a combination of mathematical, statistical, and computer science knowledge for analyzing, processing, and modeling data. This modified data is further used for the prediction of results that can help organizations come up with efficient plans that need to be executed for the company’s welfare.

These experts use their skills and techniques to extract and manage data for boosting business efficiency. They make use of their experience, contextual knowledge, current market trends, and their assumptions made on the existing data to find solutions to the current challenges that the organization is facing. To do so, they must use predictive analysis, Machine Learning (ML) algorithms, and other advanced-level analytical technologies.

Become a master in Data Science by joining this Post-Graduation Data Science program.

Let’s briefly try to gather some knowledge of what these professionals do and what their responsibilities are.

What does a Data Scientist do?


A Data Scientist must assume many roles while working in an organization, including that of an analyst, mathematician, computer scientist, and trendspotter. To fulfill these many roles on a daily basis, they have several responsibilities in the organization. Let’s take a look at some of the most common and significant ones:

  • Collect large volumes of quantitative and qualitative data and transform it into a readable and usable format

  • Use data-driven methods to resolve business issues

  • Work with Python, SAS, R, and other programming languages

  • Apply several distribution methods and statistical tests

  • Make use of Deep Learning, ML, and analytical techniques

  • Analyze patterns and trends in data to help in building business efficiency

The overall life cycle of these professionals is mentioned below:

Step 1: Discover data

Step 2: Perform ETL (extract, transform, and load) for data preparation

Step 3: Use visualization tools to apply Exploratory Data Analytics (EDA) for planning the model

Step 4: Use necessary tools to build the model

Step 5: Deliver the results using the data visualization tools

How to become a Data Scientist?

You have read about Data Scientists in terms of who they are and what they do. Now, you may wonder what steps need to be followed to become one. What are the skills and qualifications required? And so on. Let’s discuss how you can become a Data Scientist and the criteria that you need to meet.

Following are the steps that will lead you to become a Data Scientist:

  • Get a bachelor’s degree in statistics, mathematics, or computer science

  • Acquire the necessary skills expected from a Data Scientist

  • Gain practical experience as a Data Scientist

  • Enroll in a training course

Learn about the differences between Data Science and Artificial Intelligence in our comparison blog on Data Science vs Artificial Intelligence.

Moreover, you will have to work on numerous industry-specified projects that will provide you hands-on experience. Our training program offers ample opportunity to explore Data Science projects in various industries to enhance your learning experience.

If you are a student, then you must choose the right degree in the mentioned fields, complete it, and then take up our online training program. However, if you are a professional from a different background and are looking for a career transition to Data Science, Bygrad’s course on Data Science is the best for you. 

These are the skills that companies look for in a Data Scientist:

  • Mathematical and statistical skills

  • Programming skills in R, Python, etc.

  • Knowledge of PostgreSQL, MySQL, or any other database

  • Experience with data visualization tools and reporting techniques

You can also acquire these skills by taking up the course with us and can become a certified Data Scientist.

Check out the is the Difference between Machine Learning and Deep Learning.

How does Bygrad help you in making a career in Data Science?

Now, you can answer the question ‘What is Data Science?’ and know that Data Science is not all about money. It also allows you to gain immense knowledge throughout your career. So, it is this heady mix of money and deep domain knowledge that makes Data Science such an enviable career option for budding technology professionals.

Bygrad provides huge opportunities to the aspirants who are willing to establish themselves as all-rounders in this area. Hence, getting trained in Data Science technologies through courses offered by Bygrad will be the best career move you will ever make. Bygrad offers a wide range of courses dedicated to providing you with an end-to-end knowledge about the trending and highly in-demand Data Science skills in this domain.

If you want to become a Google Data Scientist at the best salary, then you need to be at the top of your game. If you are wondering how to learn Data Science and scope of Data Science, then Bygrad is just the right place to start with your incredible Data Science journey.

Check out Bygrad’s Data Scientist Online Course to get ahead in your career!

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