Difference between Data Science and Data Analytics: What You Need to Know

Data is the new oil that is influencing the global economy and as such is rather important in the modern world. Everywhere you see, you have people in important positions looking at data to make their decisions. Look at sports for example – is there any sport where data is not an important determinant? 

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Companies of all shapes, sizes, and industries are using data to make the best decisions for their business, drive revenue, and get an edge over their rivals. In this article, we will deal with the domains of Data Analytics and Data Science with a special focus on students who are looking for higher education in these fields to make a great career for themselves.

What is Data Science?

Data Science is a discipline that combines the following with specific subject matter-oriented expertise to discover actionable insights that remain hidden in an organization's data:

• statistics and maths
• artificial intelligence (AI)
• specialized programming
• machine learning (ML)
• advanced analytics

Following are the main components of data science:

• data and data collections
• machine learning (ML)
• data engineering
• programming languages
• statistical methods
• big data
• data visualization

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Data Science can help various sectors and industries in India tackle a lot of real-world problems and it is being adopted more by industries that are looking to make better-informed and more intelligent decisions. For example, in the retail sector analytics and big data are providing the retailers with insights to help satisfy their customers and make them come back to their stores. In the medical industry, physicians are wearing trackers to get important information regarding patients and thus provide them with better care. Banks are using the likes of predictive analysis and natural language processing to create virtual assistants that help customers view important information.

What is Data Analytics?

Data Analytics emphasizes performing and processing statistical analysis of existing datasets. It concentrates on creating methods to capture, organize, and process data to unearth actionable insights for present problems. It is a more focused version of data science and focuses more on actionable insights that can be applied straightaway to existing issues.

The following are the core components of data analytics:

• roadmap and operating model
• data acquisition
• data security
• data standards and governance
• insights and analysis
• data storage
• data visualization
• data mining
• pattern recognition
• predictive analysis

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Data analytics is being used across different sectors and industries to change the way organizations make decisions and function. The healthcare industry has been revolutionized by data analytics that is enabling improved care, resource optimization, and disease prevention. In the financial sector, it plays a critical role in aspects such as fraud detection, investment strategies, and risk assessment.  E-commerce platforms are using data analytics to understand customer behavior, optimize marketing campaigns, and personalize shopping experiences. Data analytics is capable of preventing and detecting cyber-attacks and threats thus playing a crucial role in the cybersecurity sector. It also improves supply chain management by optimizing inventory levels, enhancing operational efficiency overall, and reducing expenses.

Data Science vs. Data Analytics: Key Differences

Difference in terms of Focus and Objectives: This is the most fundamental area of difference when it comes to data science vs data analytics. Data analytics focuses more on visualizing and summarizing data to uncover trends. On the contrary, data science uses advanced analytical techniques to make predictions and come up with deeper insights. Data analytics is more focused on interpreting historical data so that it can find trends and patterns that can inform decisions taken by businesses. On the other hand, data science incorporates tasks that are related to data analytics but it focuses a lot more on the likes of algorithm development and predictive modeling for uncovering insights.

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Difference in terms of Required Skill Sets and Tools: Data analytics focuses more on data visualization software and statistical tools like Tableau, business intelligence software like Power BI, and Excel for connecting data sources and visualizing analytics. Domain-specific languages such as Structured Query Language (SQL) are important in this case as well. Data science, on the other hand, uses a broader group of advanced techniques and tools such as ML algorithms, advanced statistical modelling, and complex simulations for its work. You also need programming languages such as R, Apache Spark, and Python in this particular context. Deep learning, natural language processing, and neural networks are important in this context as well. With these tools, data scientists can wrangle massive datasets, refine and develop ML models at scale, and engineer features.

Difference in terms of Approach and Methodology: Data science produces broad insights by way of data exploration as well as actionable insights that answer specific questions that users may have. On the other hand, data analytics is focused more on producing insights that answer specific questions. There is a greater emphasis in this case on coming up with insights that can be put into action straight away.

Difference in terms of Jobs on Offer: Following are the top jobs you can land with a Data Science education:

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Following are the top jobs you can land with a Data Analytics education:

Educational Pathways in India

Following is a list of the top Data Science courses in India:

MBA With Specializations In Data Science, Amity Online – This specialized data science program focuses on how one can convert data into valuable business insights and provide expertise in the industry's most in-demand tools and technologies.

International Business Machines (IBM) Data Science Professional Certificate, Coursera – It describes what data science is to you and the various activities you have to perform as part of your job

Data Science Course: Complete Data Science Bootcamp, Udemy – It provides you with all the tools that you need to become a data scientist

Micro master Program in Statistics and Data Science, MIT Institute for Data, Systems, and Society and MITx – It equips you with the fundamental knowledge of the tools and methods used in data science

Executive Post Graduate Program in Data Science, up Grad – It offers specializations such as the following:

• Deep Learning
• Natural Language Processing (NLP)
• Business Analytics
• Business Intelligence/Data Analytics
• Data Engineering

Diploma in Data Science, Indian Institute of Technology (IIT) Madras – There are eight courses to choose from over here and they include hands-on training by way of projects and labs.

Following is a list of the top data analytics courses in India:

BBA With Specialization In Data Analytics, Amity Online – It is a 3-year program which equips students with the skills to collect, analyze, and interpret data to inform strategic business decisions. The curriculum generally includes training in quantitative analysis, enabling students to apply mathematical and statistical techniques to address business challenges.

BCA With Specialization In Data Analytics, Amity Online - It is also a 3-year program that offers comprehensive expertise in various aspects of data analytics, including data warehousing, modelling, mining, analytics, visualization, and reporting. This specialization allows students to engage with data across multiple dimensions, including Big Data, and equips them with the skills to design products, fostering proficiency in software and game development.

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Data Analytics Course, IIM Skills – It is a 6-month program with a couple of additional months where you can go for an optional unpaid internship program for invaluable professional experience

Full-stack Data Science, Jigsaw Academy – It is backed by Indian Institute of Management (IIM) Indore and includes important modules such as data interpretation, data manipulation, and data integration

Business Analytics 360, AnalytixLabs – The course covers all the modules that are important to data analytics along with additional modules.

Data Analyst Master Program, Simplilearn – The course teaches you to master the following:

• descriptive and inferential statistics
• hypothesis testing
• regression analysis
• data blending
• data extracts
• forecasting

Data Analysis with Python and SQL, Udacity – The program teaches students how to work with messy datasets and includes modules such as data analysis, data wrangling, practical statistics, and data visualization using Python.

Top Colleges and Universities offering Data Science and Data Analytics courses in India:

• Loyola College, Chennai
• Fergusson College, Pune
• Mount Carmel College (MCC), Bangalore
• Christ University, Bangalore
• Mithibai College of Arts, Mumbai
• Kristu Jayanti College (KJC), Bangalore
• Kishinchand Chellaram College (KCC), Mumbai
• Loyola Academy Degree and PG College, Secunderabad
• M.O.P Vaishnav College for Women, Chennai
• NMKRV College for Women, Bangalore

Choosing the right path: Data Science or Data Analytics?

You already know the difference between data science and data analytics. So, it can be expected that you would know which one would suit your interest the best, and which one would be more in line with your career goals. These are the first factors that you need to focus on when you are choosing between these two disciplines. The good thing with both data science and data analytics is that both are in demand in various industries in India with data science jobs growing rapidly. This means no matter which one you choose you would not be short of jobs. Experts expect the demand for these professionals to quadruple in the next decade which means that the future looks bright.

Conclusion

Thus, data science and data analytics are somewhat similar but there are major areas of differences between them especially in terms of focus and objectives, tools and skill sets required, the career opportunities provided to the students, and approach and methodology. When it comes to data science vs data analytics in terms of a career choice you must focus on your interests as well as demand in the job market in equal measure. Also, choose the best institutions for studying these courses such as Amity Online.

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