Syllabus
Introduction to Data Mining, The origins of Data Mining, Data Mining Tasks, OLAP and
Multidimensional data analysis, Basic concept of Association Analysis and Cluster Analysis.
Application of Business Analysis: Retail Analytics, Marketing Analytics, Financial Analytics,
Healthcare Analytics, Supply Chain Analytics.
Objectives and Outcomes
Course Outcomes:
CO1: Understanding the Role of Business Analyst and Data Science in business.
CO2: Understanding the basic concept of data management and data mining techniques
CO3: To understand the basic concept of machine learning
CO4: To understand the application of business analysis.
Introduction: What is business analytics? Historical Overview of data analysis, Data Scientist vs.
Data Engineer vs. Business Analyst, Career in Business Analytics, What is data science, Why Data Science, Applications for data science, Data Scientists Roles and Responsibility
Data: Data Collection, Data Management, Big Data Management, Organization/sources of data,
Importance of data quality, Dealing with missing or incomplete data, Data Visualization, Data
Classification Data Science Project Life Cycle: Business Requirement, Data Acquisition, Data Preparation.
CO-PO Mapping:
PO1
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PO2
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PO3
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PO4
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PO5
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PO5
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PO6
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PO7
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PO8
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PO9
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PO10
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PO11
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PO12
|
CO1
|
2
|
2
|
2
|
2
|
2
|
2
|
–
|
–
|
–
|
–
|
1
|
1
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CO2
|
3
|
3
|
2
|
2
|
2
|
2
|
–
|
–
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–
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–
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1
|
1
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CO3
|
2
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2
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3
|
2
|
2
|
2
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–
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–
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–
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–
|
1
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1
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Text Books / References
Text Books / Reference Books:
1. Essentials of Business Analytics: An Introduction to the methodology and its application,
Bhimasankaram Pochiraju, SridharSeshadri, Springer
2. Introduction to Machine Learning with Python: A Guide for Data Scientists 1st Edition,
by Andreas C. Müller, Sarah Guido, O’Reilly
3. Introduction to Data Science, Laura Igual Santi Seguí, Springer
4. Introduction to Data Mining, Pang-Ning Tan, Michael Steinbach, Vipin Kumar, Pearson
Education India
5. An Introduction to Business Analytics, Ger Koole, Lulu.com, 2019.