Data Science is a multi-disciplinary approach that combines statistics, math, and advanced programming to unfold the hidden patterns of business data. It is said that automation hit the organizational sectors due to large chunks of unprocessed data. In earlier times, most of the data accumulated by businesses were very small in numbers so it was very easy to process them using simple Business Intelligence tools. However, with the exponential growth of IT industries, it became difficult to analyze unprocessed data and that’s when data science came into existence.
Technavio report suggests that the data science market size would shoot up by USD 68.02 billion, at a CAGR of 24.73% from 2021 to 2026.
The role of data science in business endeavours is to systematically align big data using countless algorithms and techniques.
What is Data Science?
Data Science is an approach to extracting ever-increasing volumes of data collected by organizations and taking actionable insights to draw informed conclusions. It encompasses data analysis and data processing using premium techniques for stakeholders to acquire meaningful insights.
Data preparation involves data cleaning and manipulating them to boost the business value in the market. So, this requires the development of machine learning algorithms, and AI models using which data can be validated with the support of various visualization tools.
Who is a Data Scientist?
A data scientist is someone who gets involved in studying, processing, and analyzing data. He is the captain of an organization who has the power to take businesses to a higher level by predicting different possible outcomes. The data surrounding us is produced from multiple sources namely multimedia forms, financial logs, digital media, large text files, etc. To operate on a copious amount of data, we need state-of-the-art technologies that assist in deriving concrete conclusions out of it.
The popularity of data science in India increased recently due to the emergence of covid induced lockdown. A state of nothingness drew people to traverse through inordinate ideas and take up skills that will help them to foster productivity. Data Science is one of the highly regarded job-oriented programs in today’s scenario which has changed the course of job trends.
You can refer our article Who are Data Scientists?
Data Scientist Vs Data Analyst
As per the World Economic Forum, data scientist and data analyst job roles represent the most in-demand profiles across industries. With the increase in demand for plenty of data professionals, there is always confusion that surrounds in-between data scientists and data analysts.
Data Analysts work on structured data to solve tangible problems using business tools like Python, R, SQL, Statistical analysis, and visualization software.
- They mainly collaborate with business leaders to detect the informational needs.
- They get involved in cleaning and reorganizing data from primary and secondary sources.
- They present findings in a better way to make informed decisions.
Data Scientists are known for dealing with unknown or unstructured data to make future predictions. Sometimes, they automate their own algorithms or create predictive modelling processes which can manipulate both types of data. In simple terms, the data role is a more advanced version of data analysts.
- They engage in gathering, cleaning, and processing data
- They develop tools to monitor and analyze data accuracy.
- They build visualizations tools, reports, and dashboards.
Why should you learn Data Science?
Data science is widely used in all the industries these days with companies looking to enhance their market goals and find value in the data they are accumulating. These professionals are actively engaged in collecting volumes of data and deriving consequential outcomes. One of the biggest advantages of learning data science is to line up with current industry standards and learn different techniques which are used to gather, clean, filter, process, and visualize big data sets.
Evidently, data science is progressing quickly, and more and more employers are recognizing the value that it offers. As per Indeed.com, data scientists job openings have increased by 75% in three years. Even though the demand for data scientists is high, so is the competition in the market. It is a lucrative career to pursue, and more individuals are switching into this profession to get upskilled as per contemporary business standards.
Pay Scales of Data Scientist
By having less than a year of experience, an entry-level data scientist makes approximately INR 5,00,000 to 6,00,000 per year. Data Scientists with one to two years of experience can expect to earn about INR.610,811/- in a year.
As per the location, data scientist salary in India differs for instance, in Mumbai- 7lpa, Bangalore-9lpa, and Kolkata-4lpa.
You can refer below articles for data scientist salary in different regions
In other countries as well the salary differs for a data scientist, for example, the US tops the list of countries that provide high salaries to all the professionals who are willing to work with them. Australia is ranked number two in terms of high payout for data science amateurs which is succeeded by Israel, Canada, and Germany.
How to learn Data Science Certification Courses in 2022?
The initial stride towards learning data science is to consume all notable subjects like Data Science Foundation, Machine Learning, R programming, Python, Tableau, etc. While data science is the study of data, machine learning is the instrument used to carve out insights from raw data and make predictions about an event that is going to happen.
In an essence, data science could be considered a tool to formulate corporate decisions and a machine learning algorithm for deriving prophecies about a particular event using predictive and prescriptive analytics.
The next relevant aspect is to take part in capstone and client projects by joining forces with a good Artificial Intelligence (AI) company for getting hands-on experience. Most supreme thing is that data science calls for practice by working on real-time projects to supplement the theoretical knowledge of a data enthusiast.
Some of the relevant skills to become a data scientist are as follows:
- Basics of data science foundation
- Statistical and programming knowledge
- Data visualization techniques
- Analytical skills
- Software engineering
- Model deployment strategies
The duration of a data science course usually goes up to six months which includes theoretical and practical training. Around fourteen course modules should be covered to make the candidates Job Ready. These are mentioned below:-
- Data Science Foundation
- Python Essentials for data science
- R Language Essentials
- Maths for Data Science
- Data Preparation with Numpy Pandas
- Visualization with Python
- Machine learning Associate
- Advanced Machine Learning Associate
- SQL for Data Science
- Deep learning- CNN Foundation
- Tableau Associate
- ML Model Deploy- Flask API
- Big Data Essentials
- Data Science Project Execution
Data science is one of the sought-after job-oriented courses of the 21st century which is designed for professionals and students who are just out of college. It has the potential to take the corporate culture to next level incorporating all the modern mechanisms as well as impart relevant skills and knowledge to the budding talents that resonate with the current setup.
DataMites global training institute covers all the above-mentioned aspects in terms of imparting knowledge in the best possible manner. Sign up for DataMites Data Science Certification Training with no delay. DataMites top courses are accredited from IABAC.