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Did you know that Data
Science and Data Analytics are two domains that deal with a big volume of data
but are different in many ways? Yes, you heard it right! So, read this blog to
know the differences between Data Science and Data Analytics, the job
responsibilities, popular universities offering courses in Data Science and
Data Analytics and their eligibility criteria.
Key Highlights
What is Data Science?
Data Science is a
multidisciplinary field that aims to analyse structured and unstructured data
to extract meaningful information and insights. Data Science is not a part of
Data Analytics. In fact, Data Science is an umbrella term encompassing Data
Analytics, Machine Learning and other related disciplines. To put it simply,
Data Analytics is one of the branches of Data Science that focuses on solving
issues Data Science brings forth.
What does a Data Scientist do?
A Data Scientist analyses
a large volume of data for actionable insights and performs the following job
responsibilities:
In a nutshell, a Data
Scientist forecasts the future based on past patterns, whereas a Data Analyst
extracts meaningful insights from data sources. An interesting fact is that a
Data Analyst can become a Data Scientist by upskilling their mathematical and
programming knowledge and mastering machine learning algorithms.
Data Science - Course Eligibility
One of the main
eligibility criteria for pursuing post-graduate courses in Data Science is a
bachelor’s degree in Science or Engineering field from a recognised university
with a minimum of 50% marks. Do not forget to check the university-specific
requirements before enrolment.
What is Data Analytics?
Data Analytics is a
process of analysing data and drawing meaningful conclusions and insights that
help organisations improve their operational efficiencies. Companies hire Data
Analysts for this specific task.
What does a Data Analyst do?
Data Analysts use
specialised systems or software programs to perform their job responsibilities.
Some of their main job responsibilities are as follows:
Data Analytics - Course Eligibility
Having a bachelor’s
degree in Science or Computer Science from a recognised university with a minimum
of 50% marks is one of the main eligibility criteria for post-graduate Data
Analytics courses. It is a wise idea to check the university-specific as well
as other course-specific eligibility requirements before enrolling.
Key differences between Data Science and Data Analytics
Some of the key differences between these two domains are as follows:
Basis |
Data Science |
Data Analytics |
Goal |
Deals with explorations and new innovations |
Makes use of existing resources for identifying actionable
insights |
Disciplines Involved |
Mathematics, Statistics, Computer Science, Information
Science, Machine Learning and Artificial Intelligence |
Statistics, Statistical Analysis and Mathematics |
Coding Language |
Python, R, SAS, SQL, Scala, etc. |
Python and R Language |
Data Type |
Mostly deals with unstructured data |
Deals with structured data |
Proficiency |
Database management, Data wrangling and Machine Learning |
Data visualisation |
Universities offering Data
Science and Data Analytics courses
As per the U.S. Bureau of
Labour Statistics (BLS), the demand for Data Scientists and related occupations
between 2021 and 2029 is expected to grow by 30%. Considering the ever-growing
demand, many notable universities are offering post-graduate and certification
courses in Data Science and Analytics. Some of the top-ranking universities and
colleges offering such courses are as follows:
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