BUSINESS ANALYTICS | UNIT 3 DETAILED EXPLANATION | SEM 6 | BCOM | DU/SOL/REGULAR/NCWEB

Complete Guide to Business Analytics Using R | Basics to Advanced for Beginners
Welcome to our complete and easy-to-understand guide on Business Analytics using R Programming. Whether you're a student, beginner, or professional, this video is your one-stop learning solution for all the essential topics in business analytics with R.

In this video, we cover the core concepts from the basics of data and data science to practical hands-on topics like R commands, importing data, using packages, and exporting data.

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Topics Covered:

1. Data and Data Science

What is data?

Meaning and importance of data science in business analytics.



2. Data Analytics vs Data Analysis

Understanding the difference between the two terms with examples.



3. Classification of Analytics

Descriptive, Predictive, and Prescriptive Analytics explained in simple terms.



4. Applications of Analytics in Business

Real-world examples of how analytics helps in marketing, sales, finance, HR, and more.



5. Big Data and Its Characteristics

The 5 V's of big data: Volume, Variety, Velocity, Veracity, and Value.



6. Applications of Big Data

How companies like Amazon, Netflix, and banks use big data for smarter decisions.



7. Challenges in Data Analytics

Key issues like data quality, privacy, security, and skilled workforce.



8. Introduction to R

Why R is used in data analysis and its advantages in the business world.



9. Advantages of R

Free, open-source, powerful visualization and analytics capabilities.



10. Installing R Packages

Step-by-step guide to install and load useful R packages.



11. Importing Data from Spreadsheet Files

How to load CSV and Excel files into R easily.



12. R Commands and Syntax

Learn basic R commands for data manipulation and analysis.



13. Packages and Libraries in R

What are packages and libraries, and how to use them effectively.



14. Data Structures in R

Understand vectors, matrices, lists, factors, and data frames with examples.



15. Data Frames and Exporting Data

Work with data frames and save your analysis to Excel or CSV files.





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Why Watch This Video?

Beginner-friendly explanations

Covers both theory and practical examples

Useful for academic exams, projects, or real-world business problems

Step-by-step demonstrations with simple code in R



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Resources & Extras:
Download sample R code and datasets (link in comments or description)
PDF notes and cheat sheets available on request


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