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Syllabus || SNS Courseware
Subject Details
Dept     : MBA
Sem      : 3
Regul    : R2023
Faculty : Dr.P.Krishnaveni
phone  : 9942063355
E-mail  : krishnaveni.p.mba@snsct.org
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Syllabus

UNIT
1
INTRODUCTION TO BUSINESS ANALYTICS

Introduction-Analytics and Business Transformation-Classifications of Analytics-Common Applications of Analytics in Business-The Process of Analytics -Tools in the Analytics Process -Roles in an Analytics Team.

UNIT
2
THE OPPORTUNITIES AND CHALLENGE OF DATA

Introduction – Sources of Data for an Organization - From Assets and Activities to Data - Data Provenance and Data Quality - Data Logistics.

UNIT
3
DATA MECHANICS

Introduction – Data Schemas and Data Sets, Common Data Transformations and Advanced Data Transformations, Data Cleaning, Normalization, and Enhancement.

UNIT
4
DESCRIPTIVE ANALYTICS

Introduction – Power BI Fundamentals – The Contoso Dataset Analyzing Data Using Power BI – Working with Calculated Measures in Power BI – Visualization of Data – Visualization Case Study.

UNIT
5
PREDICTIVE ANALYTICS

Introduction – Predictive Analytics Workflow – Machine Learning Background – Machine Learning in Practice: Classification – Machine Learning in Practice: Regression and Recommending – Machine Learning Case Study.

Reference Book:

Witten, I. H., Frank, E., & Hall, M. A. (2016). Data Mining: Practical Machine Learning Tools and Techniques. Burlington, MA: Morgan Kaufmann. Provost, F., & Fawcett, T. (2013). Data Science for Business: What You Need to Know about Data Mining and Data-Analytic Thinking. Sebastopol, CA: O'Reilly Media. Albright, S. C., & Winston, W. L. (2022). Business Analytics: Data Analysis & Decision Making (7th ed.). Cengage Learning. Provost, F., & Fawcett, T. (2022). Data Science for Business: What You Need to Know about Data Mining and Data-Analytic Thinking (2nd ed.). O'Reilly Media. Igual, L., & Seguí, S. (2021). Introduction to Data Science: A Python Approach to Concepts, Techniques, and Applications. Springer.

Text Book:

Microsoft Corporation. (2020). Exam Ref DA-100 Analyzing Data with Microsoft Power BI. Redmond, WA: Microsoft Press. James, G., Witten, D., Hastie, T., & Tibshirani, R. (2013). An Introduction to Statistical Learning: with Applications in R. New York, NY: Springer.