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Data Analytics vs Data Science to Study Abroad
Did you know that Data Science and Data Analytics are two fields that handle a large amount of data but have distinct differences? That's right! To understand the disparities between Data Science and Data Analytics, their job responsibilities, renowned study abroad universities offering courses in these fields, and the eligibility criteria, read this blog. In today's business world, information is highly valuable, and many organizations rely on collecting, storing, and processing data to improve their business models and increase revenue. However, it can be confusing to understand the difference between Data Science and Data Analytics and which one is the right choice for you. In this blog, we will explore these details to help you make an informed decision. First, let's clarify that while Data Science and Data Analytics have different objectives, they both heavily rely on data as their main resource. These disciplines are closely related, with Data Analytics often being considered a branch or subdiscipline of Data Science.
Table Of Contents
Table Of Contents
1. What is Data Science & Data Analytics?
Data Science is a field that combines various disciplines to analyze both structured and unstructured data in order to uncover valuable information and insights. It is important to note that Data Science is distinct from Data Analytics. In fact, Data Science is a broader term that includes Data Analytics, Machine Learning, and other related fields. To put it simply, Data Analytics is a specific branch of Data Science that is dedicated to addressing the challenges posed by Data Science. Data analytics is the process of examining unprocessed data to draw conclusions and insights. By utilizing data analytics, businesses can enhance their performance, operate more effectively, increase profits, and make better-informed decisions.
2. What to choose: Data Science or Data Analytics to study abroad?
Data scientists utilize prototypes, algorithms, and predictive models to discover innovative ways of utilizing data and identifying patterns that may be valuable in the future. These efforts drive innovation and raise important questions that we may not have even considered before. On the other hand, Data analysts apply their skills to filter data, extract relevant information, and provide solutions for businesses and institutions across various sectors such as healthcare, finance, insurance, travel, and energy management. Their insights are utilized to enhance the decision-making process, establish key performance indicators (KPIs), and serve other business purposes.
2.1. Difference between Data Science and Data Analytics
Some of the key differences between these two domains are as follows:
|
Factors |
Data Science |
Data Analytics |
|
Goal |
Data Science involves exploring and experimenting with new techniques for using and understanding data |
Data Analytics focuses on analyzing datasets to uncover insights and solve problems. |
|
Disciplines Involved |
Information Science, Mathematics, Statistics, Computer Science, Machine Learning and Artificial Intelligence |
Statistics, Statistical Analysis and Mathematics |
|
Proficiency |
Database management, Data wrangling and Machine Learning |
Data visualization |
|
Coding Language |
Python, R, SQL, SAS, Scala, etc. |
R and Python Language |
Here are a few universities we recommend for Data Science and Data Analytics degrees:
- Kansas State University, the US
- University of Leeds, the UK
- Institut Polytechnique de Paris, France
- University of Europe for Applied Sciences, Germany
- Barcelona Technology School, Spain
3. Data Science VS Data Analytics Specialisations
If a general Data Science degree is too broad, there are other subdisciplines you can choose from, in addition to Data Analytics. Here are several options:
- Data Engineering
- Data Mining
- Database Management and Architecture
- Data Visualisation
- Business Intelligence
Due to constant changes in the sector and the demand for specialists with interdisciplinary skills, it’s not uncommon to find merged courses, such as Data Science and Analytics or Data Science and Business Analytics.
4. Curriculum of Data Science VS Data Analytics
The courses or subjects you will study can differ significantly from one university or country to another. That is why it is often recommended to review the curriculum of each course to ensure it aligns with your expectations.
However, we would like to provide you with an overview of what you can anticipate studying in a degree program in either Data Science or Data Analytics. Please take a look at a few examples below.
4.1. Data Science Subjects
Subjects you may study in the Data Science degree program will be:
- Discrete Mathematics
- Data Security
- Database Systems
- Intermediate Statistics
- Data Structures and Algorithms
- Principles of Data Mining
- Software Developmen
4.2. Data Analytics Subjects
Subjects you may study in the Data Analytics degree program will be:
- Pattern Recognition
- Calculus and Linear Algebra
- Data Mining
- Modeling and Statistical Decision Making
- Machines, Languages, and Computation
- Essential Statistics
- Visualization
5. Top Countries to Study Data Science and Data Analytics Abroad
For Data Science: The United States, the United Kingdom, Finland, Canada, Australia, and Germany are some of the best nations to study BSc Data Science. These nations provide highly regarded data science universities, programmes, industries, and employment prospects. Before choosing a course of action, it is advised to do some study and weigh your options.
For Data Analytics: The United States, the United Kingdom, Canada, France and Germany are some of the best nations to study BSc Data Analytics. These are the most popular destinations for all foreign students because of their strong reputation for teaching research infrastructure innovation and job opportunities in the STEM ( Science, Technology, Engineering and Mathematics) field. Before choosing a course of action, it is advised to do some study and choose your options wisely.
6. Top Universities to study Data Science and Data Analytics
Many prestigious 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:
- Massachusetts Institute of Technology, US
- Kansas State University, the US
- The University of Texas, Austin, US
- Imperial College London, UK
- University of Leeds, the UK
- Institut Polytechnique de Paris, France
- University of Europe for Applied Sciences, Germany
- Barcelona Technology School, Spain
7. Skills Needed for Data Science VS Data Analytics
We’ve listed several key abilities for each discipline. Even though there are important distinctions, keep in mind that some skills can overlap:
|
Skills |
Data Science |
Data Analytics |
|
Problem-solving |
You need Problem Solving Skills |
You need Problem Solving Skills |
|
Attention to details |
You have to be Attentive to the Details |
You have to be Attentive to the Details |
|
Software development |
Yes |
- |
|
Machine learning |
Yes |
- |
|
Proficiency |
in big data tools: Hadoop and Spark |
in R, SAS |
|
Programming abilities: Python, R, Scala |
Yes |
No |
|
Expertise in |
SQL, Cassandra, MongoDB Of visualization tools: QlikView, Tableau |
Of SQL, Excel, Power BI |
|
Database management and reporting |
Yes |
Yes |
|
Business acumen |
- |
Yes |
To stand out on the job market, you should take advantage of any internship or placement opportunity available during your studies. While your professors will do their best to teach you, nothing compares to hands-on experience and applying your knowledge in real-life scenarios.
8. Job Opportunities for Data Science vs Data Analytics
More and more companies are depending on data, which means there is a greater demand for experts who can handle and utilize data efficiently. Data Science is the third fastest-growing industry in the United States, experiencing a 37% annual growth rate. Check out the job titles and average annual salaries listed below:
8.1. Data Science jobs
Here are the Data Science job titles and average annual salaries listed below:
- Data Scientist - 79,00,000 INR
- Data Architect - 60,00,000 INR
- Data Engineer - 60,00,000 INR
- Machine Learning Specialist - 64,00,000 INR
- Statistician - 64,00,000 INR
8.2. Data Analytics jobs
Here are the Data Analytics job titles and average annual salaries listed below:
- Data Analyst - 57,00,000 INR
- Business Analyst - 57,00,350 INR
- Operations Analyst - 45,00,000 INR
- Quantitative Analyst - 88,00,000 INR
- Data Consultant - 63,00,000 INR
9. Data Science and Data Analytics Courses Abroad: Admission Process
Here is the step-by-step guidance for the complete study abroad university/ college application process for Data Science or Data Analytics that includes the following key stages thus maximizing your chances of getting admission in the institution of your choice.
Step 1: You can't get Expert Free Counseling
Step 2: Identify the Course, Country, And University of your choice
Step 3: Prepare yourself for International Test
Step 4: Complete your documents as per need of your admission process
Step 5: Complete the Application Process immediately
Step 6: Prepare yourself for Interview during the admission process
Step 7: Get your Visa Permit
10. Course Eligibility for Studying Data Science VS Data Analytics Abroad
The eligibility criteria for pursuing higher education in life science from overseas universities depend on various factors. Here are the general eligibility criteria:
10.1. Data Science
Eligibility criteria for studying Data Science Abroad:
- For pursuing post-graduate courses in Data Science is a bachelor’s degree in Science or Engineering field from a recognized university with a minimum of 50% marks.
- Do not forget to check the university-specific requirements before enrolment.
- Class 12th exams with certain subjects such as Advanced Functions, Calculus & Vectors, English, and Physics (may vary according to university).
- SAT or ACT scores (for pursuing B.Tech or BSc abroad).
- English language proficiency test scores: IELTS, TOEFL, or Duolingo score.
- Latest resume.
- Statement of Purpose (SOP).
- LORs (Letters of recommendation).
10.2. Data Analytics
Eligibility criteria for studying Data Analytics Abroad:
- For post-graduate Data Analytics courses, 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.
- It is a wise idea to check the university-specific as well as other course-specific eligibility requirements before enrolling.
- Class 12th exams with certain subjects such as Advanced Functions, Calculus & Vectors, English, and Physics (may vary according to university).
- SAT or ACT scores (for pursuing B.Tech or BSc abroad).
- English language proficiency test scores: IELTS, TOEFL, or Duolingo score.
- Latest resume.
- Statement of Purpose (SOP).
- LORs (Letters of recommendation)
11. Conclusion
Congratulations, you've reached the end! It might not be easy to absorb all this knowledge about Data Science and Data Analytics. However, now that you understand the distinction between the two, selecting a study program should be much simpler. Which of these fields interests you more, and what is your reasoning behind it? Did Data Science or Data Analytics make you reevaluate your preferences? Feel free to share this blog and provide us with your inputs!
12. WHO WE ARE
If you are planning to study abroad for next Intake 2024 and looking for further assistance, make Career Clinic your Study Abroad Consultancy partner. We offer customized education assistance for students, enabling them to pursue higher studies without hassle. So, get in touch with us today to know more. Remember, you can also apply for online assistance from us for Higher Studies in Data Science or Data Analytics.
Frequently Asked Questions
Data Science is much of a broader term is a macro topic and data analytics is a part of it. Both of these fields require separate skill sets such as data science requires the professionals to be having the knowledge of data modeling, predictive analytics programming, etc. Whereas data analytics requires knowledge of BI tools, SQL, etc. Data Analytics utilizes existing information to unravel new information or insights.
Data analytics is crucial for businesses as it allows them to enhance their performance. By integrating it into their business model, companies can identify more effective ways of conducting business, resulting in cost reduction. Moreover, data analytics enables companies to make informed decisions and analyze customer trends and satisfaction, ultimately leading to the development of improved products and services.
Data science is currently in high demand. Data Science is considered a lucrative field. Organizations are increasingly relying on data to make informed decisions, and this has created a need for professionals who possess effective data management skills. The market in the world for data science is growing rapidly and is projected to reach a value of INR 2 Trillion by 2026.
Data Analysts use specialized systems or software programs to perform their job responsibilities. Some of the main job responsibilities of a Data Analyst are as follows:
- Data Analyst Collect and interpret data for analysis.
- Data Analyst Identify relevant patterns in a dataset and translate them into actionable insights.
- Data Analyst Presents findings in an easy-to-understand format for taking informed business decisions.
