Data Science Guide 2021

By Nandini

Last updated on Aug 18 2020

Data Science Guide 2021

A Comprehensive Guide to Data Science


Data science has been the talk of the town since its arrival. There are several Data science courses that people take to become professionals in this area. It helps the companies in getting various projects and provide beneficial results. It has helped various employees in getting the job they desire and the companies in achieving the goals that they want. However, one needs to learn tons of things to become a data scientist. A single data science course is not enough for a person to become certified in data science. One needs to take up courses in various coding languages, analytical tools and big data tools so that they can know the concept of data science. Though it may sound difficult, the data science jobs are the most interesting jobs, and there are high scopes for appraisal and better job opportunities.


Data science is widely used in various areas. Be it aircraft, weather forecast or defence, data science has acquired all the fields due to its various benefits. There are people who are taking up courses on this subject to get ahead in the career. There are many online educational websites that are offering courses on this field like data science Coursera courses, courses by Udemy and many more, which can help the person in getting a data science degree online. Data science can help a person in getting a nice job in any company. Companies are looking for certified professionals in the field of data scientists who can help them in getting various projects. Moreover, data science is an area which is quite interesting as compared to other software subjects. But what exactly is data science? Why is everyone so obsessed with this part of computer science?


Data Science Definition


As the name suggests, data science is the study of data, the place from where the data came, its analysis, and the various ways in which the data can be used in various fields and create satisfactory outputs. Data science is used in various platforms for its various benefits and uses. However, data science uses tons of tools to analyze, research and store the data that the user has received. A data scientist needs to know certain tools which would help them in storing excessive data, for transferring data and even for writing the solutions for the queries. Data science is one of the major components in the software industry and is also known as the heart of every software company.


Why Choose Data Science?


This is one of the major questions that people come across while dealing with data science. Why should one use data science? There are other software and other techniques that can be used instead of data science. Then, why data science? The answer to this particular question is given in the below points.

  • Data science helps the person in finding the lead cause of the problem by asking the valid questions
  • It helps the person to perform a detailed study on the data
  • Data science helps the person in modeling the data by using various data science algorithms.
  • It helps in communicating and visualizing the results via different forms, like graphs, charts, and many more.
  • Data science has helped the industry in planning routes and deciding how to schedule the direct and connecting flights
  • It has helped in creating predictive analytics models, which would help the airline in knowing the delayed flights
  • This particular technology has helped in offering personalized promotional offers to the customers, as per the booking patterns in the flight. Due to this reason, most of the customers get some special offers or discounts while booking a flight
  • It helps the industry in deciding the class of plans on which they should invest for better efficiency and performance.
  • Data science is majorly used in the field of predictive analysis. Due to this reason, it has been useful in the field of defense of the country. They are used in submarines, ships, and even in the army. Moreover, data science helps in creating models that can help in predicting the weather of the area. 
  • Data science has helped the weather forecast companies in knowing about the calamities that are about to occur. It further helps in taking precautions which would help in saving the lives of many people.
  • Data science is even used in effective decision making. It is mainly being used in intelligent cars in which the user can collect the data and accordingly give instructions to the car to take further steps.
  • Data science has even helped the companies in getting better product recommendations. It helps the company in knowing the products which are better for the company by analyzing the data and sending it to the head of the company. 


There are other industries too which work with the help of data science. This technology has been the hot topic of the town as it helps the companies in various ways. With the help of data science, several mining plants and steel plants have also got benefits.


Data Science Applications


There are various applications of data science which the world is seeing currently. Some of the major applications of data science concepts are stated below.

  • It helps in detecting fraud, risk and credit scoring
  • It helps in the field of energy management
  • Healthcare
  • In internet search and targeted advertising
  • In recommendation systems
  • In gaming
  • Augmented reality

Apart from this, there are other data science applications too. Data science is the technology which a person uses in everyday life. It helps the person in knowing the things better and making things easier. The smartphones that a person is using for knowing the weather of another place, uses data science. Likewise, there are other examples, too, where data science is found to be applicable in daily use.


Business Intelligence Vs Data Science


Every technology has some alternative, and in the case of data science, the alternative is business intelligence. But how is data science better than business intelligence. Business intelligence is a field that focuses on the historical data of a company or a product. It uses this data to draw insights or predictions for business trends. Moreover, business intelligence helps in getting data from both internal as well as external sources, and a person can even find logical answers to business problems by using this technology.

What about data science? Data science is the technology that analyses the date from both currents as well as past data. Due to this, it helps in creating better future predictions as compared to business intelligence. It helps the businesses in knowing the answers to more open-ended questions which would help them in making wise decisions.


Data Science Vs Data Analytics


Another area that can be used as a replacement for data science is data analytics. Data analytics is a term that is often used instead of data science. These two terms are the most confusing terms, and people find it difficult to differentiate between them.

In data analytics, the scope is at the micro-level. Here, the problem of the project is already known, and the analyst is required to provide the best solution to this problem. On the other hand, in data science, the scope is of macro-level, and the data scientist tries to find and define the new problems that might occur in a business and helps in innovating something new out of the problem.

In data analytics, the input is of structured data, and the principles are designed based on the type of project. Moreover, data visualization techniques are used in the technology of data analytics. For data science, the input is basically raw or better known as unstructured data. Here, the data is cleaned and organized after which it is sent to the analyst for further steps.

Data analytics is used in healthcare, travel, tourism, finance, and similar areas. On the other hand, data science is used for internet research, image recognition, for recommendation systems, and further digital usage.


Why Should One Have A Career In Data Science?


As stated earlier, data science is a filed which has been beneficial for tons of companies in the past and is even the most needed software in global industries. A person who is building a career in data science is most likely to get a job easily in any of the companies.

As everything is slowly becoming digital, companies have started accepting data scientists and are searching for the professionals in this field. There are various courses that a person needs to take for becoming a professional in this area. There are courses on data science for beginners which can help a person in getting a job in data science entry-level. A data science entry-level salary is far more than a normal person’s salary in the software industry. However, there are other advanced courses in data science which one can get to remain updated and to learn more about this field. Advanced courses like data science masters would help the person in getting in-depth knowledge in the field. While data science basics teach the main fundamental concepts of the subject, the master course helps the person in knowing how to practically apply those concepts in real life. After completing the course, a person would be a certified data scientist and can easily get a job in any company. Data science is going to be in the market for many years, and this is one of the safest fields in which a person can make a career.

The data science career path is a path which would help the person in growing in a better way in this field. If a person is interested in data analytics and wants to know more about data and its various transformation, then data science is the field in which they should build a career.


Explore some popular Big Data course options like,


Big Data Analyst Course

Big Data Hadoop and Spark Developer Course



Who is a Data Scientist?


A data scientist is a person who recognizes important questions, collects the important data from a variety of sources, stores the data and organizes them as per requirement. Moreover, the data scientist even has to translate the data and decode them into solutions that can be used for the benefit of the business. 

Apart from all these, a data scientist is also a person who acts as a leader, is responsible for major projects in the company and is even required to provide effective results to the stakeholders. A data scientist is a technical expert in the company whose job is to maintain the data and arrange them accordingly. Moreover, they even help in untangling the code from the data and provide them to the project teams as solutions to their problems.

The data scientist has to ask the right questions in order to know the problem that the team is facing and then provide appropriate solutions. The job even includes converting the raw data into a suitable format which the project team and the stakeholders can understand. He/she is even responsible for preparing the results and providing the stakeholders with appropriate charts and results in the meetings.


Skills Required to Become a Data Scientist


Apart from data science education and degree, there are certain skills that a person should have to get a job in this field. There are certain skills that a person needs to have to become a successful data scientist. While some are software skills or technical skills that are mandatory for the person, there are also non-technical skills that a person should have to become a good data scientist. Below are the skills that are considered important for becoming a data scientist.


Python Coding: The first essential skill that a person requires to become a data scientist is python coding. Coding is important for a person who is entering the field of software, and when it comes to data science, which is one of the core subjects in software, it is quite important to know to code. Python is majorly used for analysing and researching for data. It is one of the most used software languages, and a person should know how to do coding in this language. Though there are courses in data science on various websites, it is highly suggested that a person should take up a separate course for learning Python. It would help the person in understanding the language in a better way and hence would help in getting a grasp over the subject.


R Programming: The next important skill is R programming. This is an analytical tool that is used by data scientist in many companies. It is designed mainly for the use of data science. It helps the person in knowing the problem and the ways in which he/she can solve the problem within some time. Most of the data scientists use R programming for solving the statistical problems and have found success in it. This particular tool is taught in courses of data science as it is considered as an important tool for a data scientist.


SQL Database: SQL database is designed to help the data scientist in getting access to the data. Not only that, it even helps the data scientist knows how to communicate and work on the data given to him/her. Though SQL is not considered that important as it is not a major part of data science, a company expects the data scientist to know how to write and execute the various queries in SQL. It helps the person in knowing how to carry out various algebraic operations and analytical functions. Moreover, SQL will help the person in knowing better about relational databases. 


Hadoop Platform: Hadoop has been considered as a skill that a person should have if he/she is opting for a career in data science. Hadoop platform has been in the market for years and has proven to be highly useful to data scientists in many ways. It has helped the data scientists in sending various data to other servers and for expanding the memory of the system to store the data. A person who knows how to work on the Hadoop platform would find it easy to wok on data without worrying about space or other problems. It even helps in the area of data filtration, sampling, and even exploration of data.


Get Big Data Hadoop Analyst Certification Training


Machine Learning & Artificial Intelligence: These two are the most important things that a data scientist should know. As stated earlier, data science is mainly used in aircraft, ships, and submarines. It is important to know machine learning and AI as it would help the scientists in working on these areas. Moreover, Machine learning would help the person in having solving skills so that they can solve the problems and make better predictions for the companies. In the case of intelligent vehicles, Artificial intelligence is very much important as it would help the data scientist in giving orders to the vehicles.


Apache Spark: Apache Spark is a big data technology that is being used all over the world. It is mainly used because of its benefits. With a similar framework as Hadoop, Apache spark is designed to help the person in running the complex algorithm with much more speed. With that, the data scientist would be able to get faster results and provide them to the teams for further process. Moreover, it helps the data scientists in avoiding any kind of loss in data, which can result in any loss for the projects. With the help of Apache Spark, a data scientist can analyze data and even distribute it with other servers.


Data Visualisation: Another important software skill that a data scientist should have is data visualization. It would help the person in visualizing the data with the help of various visualizing tools. It would further help the person in analyzing the data in a better way and then decode it to further provide the project team with various solutions to the problems. Moreover, data visualization would even help the person in knowing the serial correlation or p values in a better way.


MATLAB: This is a numerical solving software which is used for processing complex mathematical operations. It is highly used in data science due to its various benefits. One of the major benefits is that it can do any kind of complex equation within minutes and provide the data scientist with the appropriate results.

Apart from the technical skills, there are some non-technical skills too that a data scientist should have. Some of the most important non-technical skills are stated below.


Curiosity: Having curiosity is good for a data scientist. A person who has intellectual curiosity is a person who is more likely to get a solution for a problem faster than other people. A data scientist should always be up for learning new things that can help him/her in getting better results in the projects. With the change in time, new technologies are coming to the world. Everything is getting updated, and a data scientist should also remain updated all the time. It would help him/her in getting knowledge about the new technologies which can help him/her in the future.


Communication Skills: A person who only knows the technical terms with no good communication skills is a person who would find it difficult to adjust to any company. Having good communication skills is essential in every field of work. A data scientist needs to have good communication skills as he/she is required to give regular presentations to the stakeholders about the results of the projects, and so on. If a person does not have efficient communication skills, then he/she would find it difficult to conduct the meeting and clear the queries. Hence, a person should acquire this particular skill as it will help him/her in adapting to a company.


Teamwork: A data scientist is a person who needs to work with a team. If he/she does not know how to work in a team, then it would be difficult for the person as well as the company. Here, teamwork is important as it would help in lessening the burden and working together to solve the problems. A person needs to communicate well and know how to adjust to a team while working on a project. A data scientist needs to have the qualities that are required to work in a team, one of which is teamwork.


Business Acumen: A data scientist should also have some knowledge about business as at the end of the day they are working in a business company and are required to provide solutions to the problems. Having business knowledge would help the data scientist in thinking out of the box solutions which would benefit the business in a better way and would even help them in acquiring more projects. Hence, companies look for data scientists who know about business and the workflow in various areas.


Other Roles In Data Science


Apart from data scientist, there are other roles too which one can find in the field of data science. The two most important roles that are found in data science are discussed below.


Data Science Analyst: The first role is that of the data analyst. The role of the data analyst is to act as a communication bridge between the data scientists and business analysts. These people work on specific problems or queries and then find the results by organising and analysing the various data in the storage. They have the job of translating the technical analysis into action items and then provide them to the stakeholders for further process. 


Data Science Engineer: A data science engineer has the job of managing a bulk amount of data which keeps on changing rapidly. These people need to manage the various data pipelines and infrastructure of the data so that they can transform and transfer the data to the specific data scientist for further work. In simple language, the data engineer is a person who is responsible for providing the data scientist with the correct amount of data to work one. Without data engineers, the data scientist will not be able to get the correct data for working and hence there would be problems.


These were some of the major skills that a person who wants to become a data scientist should have. Apart from this, a person should opt for a data science course that would help him/her in getting certified. Not only that but having a practical hand in the field of data science would also be beneficial. There are various data science internships that many companies are offering, which would help the person in getting practical knowledge in the field. Furthermore, it would help the data scientist in knowing the areas in which they need to improve and the areas in which they can benefit. By doing an internship in the field of data science, a person gets to know how to critically think about a problem and create a solution for the same.


There are various data science courses that offer data science degrees, but not all courses are good enough. One needs to research well about the courses and then enrol for a course. There are courses for data science and analytics, for data science algorithms and many more. However, it is highly advised that a person should first take up courses in the essential coding languages that are required in the field of data science. By taking a course in a coding language, the person would be able to get the upper hand while doing the course for data science. As data science also requires coding experience, and most of the courses do not even teach coding, it would be better to get a coding course first. Apart from that, there are several data science books which are quite helpful for the students who aspire to become data scientists. These books are designed or curated by the experts in the field and would help the person in getting enough knowledge in data science. Not only that, a person even needs to update his/her knowledge in data science. As mentioned earlier, technology changes every day, and with the change in technology, a person also needs to update his/her knowledge. In the case of data scientists, they need to continuously update themselves and learn new skills that are required for the job. 

For more awareness about data science, you can explore DASCA


To explore certification programs in your field, chat with our experts, and find the certification that fits your career requirements. 


Suggested Reads:

Data Science vs Data Analytics vs Big Data - Detailed Explanation and Comparison

Big Data Guide - Benefits, Tools and Career Scope




About the Author

Sprintzeal   Nandini

With over 3 years of experience in creating informative, authentic, and engaging content, Nandini is a technology content writer who is skilled in writing well-researched articles, blog posts, newsletters, and other forms of content. Her works are focused on the latest updates in E-learning, professional training and certification, and other important fields in the education domain.

Recommended Courses

Recommended Resources

Operation Manager Interview Questions and Answers 2021

Operation Manager Interview Questions and Answers 2021


10 Reasons Why You Should Get PRINCE2 Certification in 2021

10 Reasons Why You Should Get PRINCE2 Certification in 2021


Lean methodology, Six Sigma methodology and Lean Six Sigma Explained

Lean methodology, Six Sigma methodology and Lean Six Sigma Explained