A Comprehensive Guide for Beginner’s To Data Science and Analytics

Introduction 

  • Data science is currently the buzzword in the information technology space, as it represents the effective use of computers. Due to the evolution of big data and the impact it has in so many industries, the demand for data scientists globally has skyrocketed compared to what we used to have like two decades ago.
  • If you are considering a career in data science and you don’t know where or how to get started, hey, why not take a chill pill and smile because you are in the right place. In this article, we will explore different segments of data science and also highlight the career prospects of a Data Scientist. 
  • But before we dig deeper, let’s quickly take a look at the meaning of data science. 

What Is Data Science?

  • Simply put, data science can be defined as the process of gathering, storing, interpreting, and analyzing data. Organizations use the concept of data science to make critical business decisions as they scale out their marketing techniques.
  • We can also define data science as a multi-disciplinary field where scientific methods are leveraged to extract insights and knowledge from unstructured/structured data.
  • Truth be told; there is data science everywhere, from purchasing goods on Amazon to streaming videos on Netflix, data is being exchanged. 

So, Why Study Data Science?

  • Since data science is the oil that powers all industries; its importance is very glaring for everybody (whether experts or novice) to see.
  • Let’s see an example of the usage of data science – when you book a cab via the Uber app, you get to know the fare and the estimated time of arriving at your destination.
  • How is it possible for the Uber app to display such information? The answer is data science! This is just an example of data science, let’s see other points:
    • Industries the world over need data to implement their policies and data science transforms raw data to factual or meaningful insights. Industries such as finance, healthcare, business, Banks, as well as startups rely so much on data science.
    • Data science is now one of the most lucrative careers to look out for. Industries are hiring Data Scientists to help them interpret data so that they can make an informed decision. 
    • Data science aids better marketing: Businesses use data science to analyze their marketing strategies, plus run advertisement ahead of their competitors. Data science also helps them to see where they need improvement. 

Why Become a Data Scientist?

  • According to Glassdoor and Forbes, Data Scientist is one of the most sought-after careers across the world as of 2018. Since data is the life wire of all industries, small and medium-sized companies now hire the services of Data Scientists. However, there are a limited number of qualified Data Scientists to fill the available vacancies. 
  • In the coming years, the need to hire Data Scientists will continue to increase. As a matter of fact, LinkedIn listed this profession as the most lucrative career in 2017 and 2018. LinkedIn also listed skills related to data science as the most sought-after by companies. 

Data Science Course Benefits

The following are the benefits of studying Data science as a course at the university or college:

1. Data science is in high demand

  • If you graduate with a degree in data science, you are one step away in securing a job as a Data Scientist. LinkedIn projected that by 2026 over 11.5 million data scientist-related jobs would be created globally. 

2. There is an Abundance of Positions

  • If you take a look at the job market, data science is one of the fields with less saturation. For this reason, data science is ahead of other sectors in the world of IT.  

3. A Highly Paid Career

  • The salary earned by entry-level Data Scientists, according to Glassdoor is ₹ 508, 682 per annum based on 56 salaries. There are only a few careers that can pay this much. This makes data science one of the most highly paid careers in India. 

4. Data Science is very Versatile

  • The impact of data science can be felt in so many industries, including consultancy services, banking, e-commerce, and healthcare. This means you can work in any industry. 

5. No More Boring Tasks

  • Since industries started hiring Data Scientists, the issue of boring tasks is now a thing of the past. The industrial process from raw material to end product is now automated, thus simplifying the difficult tasks usually being carried out by human beings. 

Difference Between Data Science And Data Analytics

  • We have already defined data science above, let’s see now see the meaning of data analytics before highlighting the differences. 

What Is Data Analytics?

  • Data Analytics concentrates on performing or processing statistical analysis using existing data. The major responsibility of a Data Analyst is to create and organize data into actionable insights geared towards solving problems.
  • Let’s simplify it further; data analysis focuses on solving challenging problems. It also encompasses statistics that help to identify the different sources of data. 

 So, What’s The Difference Between Data Science and Data Analytics? 

  • Even though a lot of people use both terms interchangeably, the fact still remains that Data science and data analytics are different in their scope. Data science is a group of fields used to mine big data. On the other hand, data analytics is an integral part of data science. For the most part, data analytics is focused on actionable insights to answer existing questions. 
  • Exploration is another notable area where the difference between data science and data analytics exist. Data science doesn’t answer specific questions, instead, it is meant to parse through raw data to expose insights.
  • Data science, more importantly, is concerned with finding answers to existing data. Plus, it is focused on finding ways to model and analyze data.  
  • More importantly, data science is more concerned about asking questions than finding specific answers. The field is focused on establishing potential trends based on existing data, as well as realizing better ways to analyze and model data.
  • The table below clearly explains the difference between these two fields. 

Difference between data science and data analytics

Data Science Skills

  • Statistics
  • At least one programming language – R/ Python
  • Data Extraction, Transformation, and Loading
  • Data Wrangling and Data Exploration
  • Machine Learning Algorithms
  • Advanced Machine Learning (Deep Learning)
  • Big Data Processing Frameworks 
  • Data Visualization

Tools/Skills Used in Data Science

  • The table below shows the tools/skills that are frequently used in data science.

Tool/Skills used in Data Science

Best Data Science Courses in India

  • The table below shows the best data science courses in India and the universities/colleges where you can study them.

Best Data Science Courses in India

Program Duration

  • The course duration span 20 weeks, plus an additional 4 weeks of project work. 

Data Science Jobs

  • The following highlights the type of jobs available in data science and the skills required to secure the jobs:

1. Data Scientist

  • A Data Scientist has the technical know-how to mine, refine, and clean data. Organizations hire Data Scientists to analyze big data to enable them to formulate policies.
  • Skills Required: Mathematical and Statistical skills, programming skills (Python, R, and SAS), Hadoop, Machine Learning, SQL, Storytelling and data visualization. 

2. Data Analyst

  • The role of a Data Analyst is to bridge the gap between a business analyst and a Data Scientist. They are also responsible for technical analysis and communicating the same to relevant stakeholders.
  • Skills Required: Data visualization, data wrangling, Mathematical and Statistical skills, and programming skills (Python, R, and SAS). 

3. Data Engineer

  • Data Engineers manage rapidly changing big data. They also concentrate on the development, management, deployment, optimization as well as the transfer of data to a data scientist for further querying.
  • Skills required: Frameworks (Apache Hadoop), NoSQL databases (Cassandra DB and MongoDB), and programming languages (Scala and Java).

4. Business Intelligence (BI) Developer 

  • BI Developers use software to translate data into meaningful insights for organizations to take action.
  • Skilled Required: SQL Programming, Domain and business knowledge, Data warehouse and concept, data collection and management, and problem-solving skills. 

5. Data Architect

  • A Data Architect has a robust knowledge of data modeling and data design.
  • Skills Required: Applied Math and Statistics, Data visualization, Data migration, Database management system software, Databases (Cloud computing and NoSQL), as well as RDMSs (relational database management systems) or foundational database skills.

6. Machine Learning Engineer

  • Machine Learning Engineers work hand in hand with Machine Learning Scientists to leverage artificial intelligence for the benefits of organizations.
  • Skills Required: Probability, data modeling, programming, Data visualization, data wrangling, Mathematical and Statistical skills, and programming skills (Python, R, and SAS).

7. Statistician

  • Statisticians gather and explain data to organizations to enable them to make marketing decisions.
  • Skills Required: Creative thinking, Maths and Data visualization, and programming skills.

Data Science Fresher Jobs

  • Entry-level Business Intelligence Developer
  • Entry-level Data Architect
  • Entry-level Applications Architect
  • Entry-level Infrastructure Architect
  • Entry-level Enterprise Architect
  • Entry-level Data Analyst
  • Entry-level Data Scientist
  • Entry-level Data Engineer
  • Entry-level Machine Learning Scientist
  • Entry-level Machine Learning Engineer
  • Entry-level Statistician

Data Science Salary In India

  • If you just graduated from University or college with a degree in Data Science and you land a job in a good company, your starting salary per annum, according to Glassdoor is ₹ 508, 682. This figure was arrived at after sampling 56 salaries. 

The Future Of Data Science

  • The field of data science is very broad and it encompasses innovative tech concepts such as Deep Learning, the Internet of Things, and Artificial intelligence, among others. The impact of data science across the world cannot be overemphasized and doesn’t seem to slow down in the years to come. 

Final Thoughts

  • If you are looking to take up a career in the field of data science and you are still in doubt where to start from, feel free to talk to us using the comment box below, and we assure you of quick response. 

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