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CCW331 – Business Analytics Full Lecture Notes | Complete Study Material

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These are comprehensive lecture notes for the course CCW331 – Business Analytics. The content is clearly organized with concepts, examples, case studies, and diagrams, making it perfect for exam preparation, assignments, projects, and quick revision. Covers complete Business Analytics syllabus Includes statistical models, data visualization, forecasting, and decision-making techniques Well-structured with theories + practical applications Useful for engineering, management, and data-related courses Designed for easy learning and exam success

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An seE

SUBJECT CODE:CCW331


Strictly as per Revised Syllabus of
ANNA UNIVERSITY
Choice Based Credit System (CBCS)
Vertical - 1 (Data Science) (CSE/IT/CSeBS)
Vertical - 1(Verticals for AIDS I) (AlaDS)
Semester VI(CS&BS)

BUSINESSANALYTICS
Dr. Arati Dandavate
s
Ph.D. (Computer Science &Engineering),
6'

M.E. (Computer), B.E. (Electronics &Communication)
F1


HOD (CE Dept.),
DPES, Dhole-Patil College of Engineering, Pune.

Dr. M. Kiruthiga Devi
Pn.D. (CSE), M.E. (Mobile ond Pervasive Computing), B.E. (CSE),
Associote Professor,
Department of Information Technology
Dr. M.G.REducationgl and Research Institute
Chennai.

Manisha Mehrotra
M.Tech. (CSE),B.Tech. (CSE),
Assistant Professor,
Dhole Patil College of Engineering,
Pune.




TECHNICAL
PUBLICATIONS
SINCE 1993
An Up-Thrust for Knowledge

, SYLLABUS
Business Analytics - (CCW331)

UNIT I INTRODUCTION TOBUSINESS ANALYTICS
Analytics and Data Science - Analytics Life Cycle - Types of Analytics - Business Problem Definis:.
- Data Collection - Data Preparation - Hypothesis Generation - Modeling - Validation and Evaluos:
-Interpretation - Deployment and Iteration. (Chapter - 1)
UNIT II BUSINESS INTELLIGENCE
Data Warehouses and Data Mart - Knowledge Management - Types of
Decisions - Decision Making
Process - Decision Support Systems Business Intelligence OLAP -
- Analytic functions
(Chapter - 2)
UNIT II BUSINESS FORECASTING
Introduction to Business Forecasting and Predictive analytics - Logic and Data Driven Models- Data
s
Mining and Predictive Analysis Modelling -Machine Learning for Predictive analytics.(Chapter - 3)
6'
F1


UNIT IV HR& SUPPLY CHAIN ANALYTICS
Human Resources - Planning and Recruitment - Training and Development - Supply chain network -
Planning Demand, Inventory and Supply - Logistics - Analytics applications in HR & Supply Chain -
Applying HR Analytics to make a prediction of the demand for hourly employees for a year.
(Chapter - 4)
UNIT V MARKETING & SALES ANALYTICS
Marketing Strategy, Marketing Mix, Customer Behaviour - selling Process Sales Planning
Analytics applications in Marketing and Sales - predictive analytics for customer's
behaviour u
marketing and sales. (Chapter - 5)




(iv)

, TABLE OF CONTENTS
UNIT I
Chapter - 1 Introductionto Business Analytics (1- 1)to (1 - 40)
1.1 Business Analytics : Introduction 1-2
1.1.1 Data Science. 1-3
1.1.2 Business Analytics andData Science - Comparison 1-4

1.2 Analytics Life Cycle 1-5
1.3 Types of Business Analytics. 1-7
1.3.1 Components of Business Analytics. .1-8
1.3.2 Applications of Business Analytics .1-10
1.3.3 Terminologies. .1 -11
1.3.4 Three Stages of Business Analytics .1-13
s
1.3.5 Process ...1-14
6'

1.3.6 Importance. .1 -16
F1



1.3.7 Scope of Business Analytics 1 -17

1.3.8 Benefits of Business Analytics. .. 1-19
1.3.9 Challenges of Business Analytics.. ..1 -20

1.3.10 Business Analytics Examples .1-22
1.3.11 Business Analytics Tools. .1 -24
1.3.12 Business Analytics Vs Data Analytics.. 1 -25

1.4 Business Problem Definition 1-26
1.5 Data Collection 1- 28

1.6 Data Preparation 1-29
1.7 Hypothesis Generation 1-30
1.8 Modeling.. 1-32

1.9 Validation and Evaluation ... 1 - 33

1.10 Interpretation 1- 34


(v)

, Deployment and Iteration 1-36
1.11
1.12 Two Marks Questions with
Answers

UNIT II
. .1-37
(2 - 1) to (2- 52
Business Intelligence
Chapter - 2
2.1 Data Warehouses and Data
Mart.... .2-2
2.1.1 Data Warehouse -
Introduction .2-3
2.1.2
Data Warehouse Components. 2-5
2.1.3 Data Mart ..2-6
2.1.4 Cost Effective Data Mart ..2-8
2.1.5 Designing Data Marts.. ..2-10
2.1.6 Cost of Data Marts .2-11
2.1.7 Data Mart versus Data warehouse ...2-13
2.2 Knowledge Management .2-15
2.2.1 Key Elementsof Knowledge Management .2-16
2.2.2 Knowledge Management Process ... 2-18
s
6'

2.2.3 Knowledge Management Tools. .2-19
F1



2.2.4 Knowledge Management Use Cases ...2-20
2.3 Types of Decisions .... 2 - 21
2.4 Decision Making Process ... 2 - 23

2.4.1 Decision-making Methodologies and Frameworks. .2-24
2.4.2 Challenges in the Decision-Making Process... .2-25
2.5 Decision Support Systems 2-27
2.5.1 Challenges in Decision Support Systerms. ...2 -28
2.5.2
Advantages and Disadvantages of Decision Support Systems... ...2 - 29
2.5.3
Applications of Decision Support Systems. ...2 -31
2.6 Business Intelligence 2-32
2.6.1
Importance of Business Intelligence .2-34
2.6.2
Examples of Business Intelligence System used in 2-35
Practice..
2.6.3
Advantages of Business Intelligence ..2 -
37




(vi)

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