UNIT I – Introduction to Data Analytics
Data Analytics – Data Analytics Different From Data Science – The Importance of Data Analytics in Today’s World – Brief History of Data Analytics – Key Concepts in Data Analytics – Data Collection and Management: Planning for Data Collection ᎓ Sources of Data ᎓ Types of Data ᎓ Data Preprocessing ᎓ Data Storage and Retrieval
UNIT II – Types of Data Analytics
Descriptive Analytics ᎓ Inferential Analytics ᎓ Predictive Analytics ᎓ Prescriptive Analytics – Techniques and Tools for Data Analytics: Data Analytics Techniques – Data Analytics Tools
UNIT III – Data Analytics Process
The Data Analytics Process – Defining the Questions – Collecting Data ᎓ Cleaning the Data ᎓ Analyzing the data ᎓ Visualizing and Sharing the Findings ᎓ Big Data Analytics: Challenges of Big Data Analytics ᎓ Technologies for Big Data Analytics
UNIT IV- Introduction to R
Features of R ᎓ How to Install R – How to Run R ᎓ Comments in R – Reserved Words ᎓ Identifiers ᎓ Constants ᎓ Variables ᎓ Operators ᎓ Strings ᎓ Data Types & Operations: Basic Data Types ᎓ Vectors – Lists
UNIT V- Charts and Graphs
Bar Charts ᎓ Histogram ᎓ Scatterplot ᎓ Connecting R to External Interfaces: CSV Files ᎓ XML Files ᎓ JSON Files ᎓ Binary Files
TEXT BOOKS
- Bianca Szasz, Data Analytics Essentials, Vibrant Publishers, First Edition, 2024, ISBN: 9781636511184
- Jeeva Jose, Beginner᎙s Guide for Data Analysis Using R Programming, Khanna Book Publishing Co. (P) Ltd, 2019, ISBN: 978-93-86173-45-4
REFERENCE MATERIALS
- Hadley Wickham & Garrett Grolemund, R for Data Science, O᎙reilly Publication, 2017, First Edition, ISBN: 978-1-491-91039-9
- Robert J.Woz, Data Analytics for Beginners: A Beginner’s Guide to Learn and Master Data Analytics, Kindle Edition,
E-RESOURCES