ip business intelligence

Lovely Professional University, PunjabCourse Code Course Title Course Planner Lectures Tutorials Practicals CreditsMGN646 BUSINESS INTELLIGENCE 15842::Amitesh Kapoor 3.0 0.0 0.0 2.0Course Category Courses with conceptual focus

TextBooks Sr No Title Author Edition Year Publisher NameT-1 DECISION SUPPORT AND

BUSINESS INTELLIGENCE SYSTEMS

TURBAN E, SHARDA R, ARONSON J E, LIANG T P

9th PEARSON

Reference BooksSr No Title Author Edition Year Publisher NameR-1 BUSINESS INTELLIGENCE FOR

THE ENTERPRISESMIKE BIERE 1st PRENTICE HALL

R-2 DECISION SUPPORT AND DATA WAREHOUSING SYSTEMS

MALLACH E.G 1st TATA MCGRAW HILL

Other Reading

Sr No Journals articles as Compulsary reading (specific articles, complete reference)OR-1 Developing a customized Decision support system for brand managers (Available in course file and Jstor) , OR-2 A Visual Framework for Knowledge Discovery on the Web (Available in course file and Jstor) , OR-3 Record Matching in Data Warehouses (Available in course file and Jstor) , OR-4 Data Mining: Statistics and More? (Available in course file and Jstor) , OR-5 Employee Reactions to Internet Monitoring (Available in course file and Jstor) , OR-6 Knowledge Management: An Organizational Capabilities Perspective (Available in course file and Jstor) , OR-7 The Dynamic Structure of Management Support Systems (Available in course file and Jstor) , OR-8 Application case on Intelligent Price setting Using an ADS, Text book 1,pg 17 , OR-9 Case on Real Time Data Warehousing at Overstock com, Textbook 1, pg 249 ,

LTP week distribution: (LTP Weeks)Weeks before MTE 7Weeks After MTE 0Spill Over 7

Week Number

Lecture Number

Broad Topic(Sub Topic) Chapters/Sections of Text/reference books

Other Readings,Relevant Websites, Audio Visual Aids, software and Virtual Labs

Lecture Description Learning Outcomes Pedagogical ToolDemonstration/ Case Study / Images / animation / ppt etc. Planned

Live Examples

Week 1 Lecture 1 Decision Support Systems and Business Intelligence(Changing Business Environment and Computerized Decision Support)

T-1:Ch-1 OR-1 Lecture Zero, Introduction of the topic discussing examples of how companies like Toyota use Business Intelligence

To analyze and explain the concept and need for computerized Decision support system

Discussion using PPT

Decision Support Systems and Business Intelligence(Concept of Decision Support System)

T-1:Ch-1 OR-1 Introduction of the topic To analyze and explain the concept and need for computerized Decision support system


Decision Support Systems and Business Intelligence(Framework for Business Intelligence)

T-1:Ch-1 OR-1 The pillars of Business Intelligence

To analyze and explain the concept and need for computerized Decision support system

Discussion using Examples

SAP BI solutions

Lecture 2 Decision Support Systems and Business Intelligence(Managerial Decision Making)

T-1:Ch-1 OR-1OR-8

Concept of management decision making

To apply the techniques of Decision Support System

Discussion using article and power point presentation

Decision Support Systems and Business Intelligence(Computerized Support for Decision Making)

T-1:Ch-1 OR-1OR-8

Over view of the tools used and their importance



Decision Support Systems and Business Intelligence(Major Tools and Techniques of Managerial Decision Support Tools)

T-1:Ch-1 OR-1OR-8

Over view of the tools used and their importance



Microsoft solutions

Lecture 3 Decision Support System Concepts(Decision Support System Configuration)

T-1:Ch-3 DSS configurations To compare BI and DSS and appreciate their characteristics


Decision Support System Concepts(Decision Support System Description)

T-1:Ch-3 DSS and BI system comparision

To compare BI and DSS and appreciate their characteristics


Decision Support System Concepts(Decision Support System Characteristics and Capabilites)

T-1:Ch-3 OR-7 Characteristics and Capabilites

To compare BI and DSS and appreciate their characteristics


Detailed Plan For Lectures

Week 1 Lecture 3 Decision Support System Concepts(Decision Support System Classifications)

T-1:Ch-3 Classifications of Decision Support System

To apply the classifications in practical life


Week 2 Lecture 4 Decision Support System Concepts(Components of Decision Support Systems)

T-1:Ch-3 Components To integrate components


Decision Support System Concepts(The Decision Support System User)

T-1:Ch-3 DSS User To appreciate the unique role of user

PPT and discussion using example

LPU UMS

Lecture 5 Data Warehousing(Concept of Data Warehousing)

T-1:Ch-7 OR-3 Concept To integrate warehousing with BI


Data Warehousing(Data Integration and Extraction Transformation and Load (ETL) Process)

T-1:Ch-7 Concept To integrate warehousing with BI


Lecture 6 Data Warehousing(Data Warehouse Development)

T-1:CH-7 Development, Administration, issues

To identify the issues and see the scope for development

PPT and Case discussion

Data Warehousing(Real Time Data Warehousing)




Data Warehousing(Data Warehouse Administration and Security Issues)




Week 3 Lecture 7 Business Performance Management(Overview of Business Performance Management)

T-1:Ch-8 Overview, Methodologies

To measure the performance of a business


Business Performance Management(Performance Measurement)




Business Performance Management(Methodologies of Business Performance Management)




Lecture 8 Business Performance Management(Architecture and Applications of Business Performance Management)

T-1:Ch-8 OR-9 Dashboards, Application of BPM

To apply BPM in their projects


Overstock com

Business Performance Management(Performance Dashboard)

T-1:Ch-8 Dashboards, Application of BPM


PPT, Discussion

Business Performance Management(Business Activity Monitoring)

T-1:Ch-8 Dashboards, Application of BPM


PPT, Discussion

Week 3 Lecture 9 Data Mining for Business Intelligence(Data Mining Concepts and Applications)

T-1:Ch-5 Concepts and Application

To apply data mining in a company


Data Mining for Business Intelligence(Data Mining Applications)

T-1:Ch-5 Concepts and Application

To apply data mining in a company


Week 4 Lecture 10 Data Mining for Business Intelligence(Data Mining Process)

T-1:Ch-5 Methods, tools, myths To apply methods and be cautious of blunders

PPT, Discussions

Data Mining for Business Intelligence(Data Mining Methods)


PPT, Discussions

Data Mining for Business Intelligence(Data Mining Software Tools)


PPT, Discussions

Data Mining for Business Intelligence(Data Mining Myths and Blunders)


PPT, Discussions

Lecture 11 Knowledge Management(Introduction to Knowledge Management)

T-1:Ch-10 OR-6 Introduction, Activities To evaluate the knowledge


Knowledge Management(Organisational Learning and Transformation)

T-1:Ch-10 Introduction, Activities To evaluate the knowledge


Knowledge Management(Activities of Knowledge Management)

T-1:Ch-10 Introduction, Activities To evaluate the knowledge


LPU UMS

Lecture 12 Homework,Test1Week 5 Lecture 13 Information Technology in

Knowledge Management(Success and Failure Factors of Knowledge Management System)

T-1:Ch-10 OR-2 System, Role of people To synthesize the knowledge with BI


Information Technology in Knowledge Management(Role of People in Knowledge Management)

T-1:Ch-10 System, Role of people To synthesize the knowledge with BI


Lecture 14 Advanced Intelligent Systems(Machine Learning Techniques)

T-1:CH-12 Techniques, Reasoning To incorporate the cases and provide similar solutions to present problems

PPT, Case Discussion

Week 5 Lecture 14 Advanced Intelligent Systems(Case Based Reasoning)

T-1:CH-12 L14 Techniques L15 Reasoning

L14 To incorporate the cases and provide similar solutions to present problems



Lecture 15 Advanced Intelligent Systems(Case Based Reasoning)

T-1:CH-12 L14 Techniques L15 Reasoning




Week 6 Lecture 16 Advanced Intelligent Systems(Intelligent Agents)

T-1:Ch-12 Intelligent agents To evaluate how IA use knowledge

Discussion using Examples

Lecture 17 Trends in Management Support Systems(New BI Application Opportunities)

T-1:Ch-13 Opportunities, Virtual Communities

To evaluate the BI opportunities

Discussion using examples

Oracle solutions

Trends in Management Support Systems(Reality Mining)




Trends in Management Support Systems(Virtual Communities)




Lecture 18 Trends in Management Support Systems(Basics of Online Social Networking)

OR-5 L18 Social Networking, ImpactL19 Revision

L18 To apply the information available in various resources to develop a BI systemL19 To clear doubts


Trends in Management Support Systems(Issues of Legality, Privacy and Ethics)

OR-7OR-8

L18 Social Networking, ImpactL19 Revision

L18 To apply the information available in various resources to develop a BI system L19 Student will be able to clear doubts

PPT and discussion

Trends in Management Support Systems(Overview of Impacts of MSS)


L18 To apply the information available in various resources to develop a BI systemL19 Student will be able to clear doubts


FLIPKART

Week 6 Lecture 18 Trends in Management Support Systems(MSS Impacts on Organizations)



PPT and discussion Myntra and Flipkart

Trends in Management Support Systems(MSS Impacts on Individuals)



PPT and discussion

Week 7 Lecture 19 Trends in Management Support Systems(MSS Impacts on Individuals)



PPT and discussion

Trends in Management Support Systems(MSS Impacts on Organizations)



PPT and discussion Myntra and Flipkart

Trends in Management Support Systems(Overview of Impacts of MSS)


L18 To apply the information available in various resources to develop a BI systemL19 Student will be able to clear doubts


FLIPKART

Trends in Management Support Systems(Issues of Legality, Privacy and Ethics)

OR-7OR-8



PPT and discussion

Trends in Management Support Systems(Basics of Online Social Networking)

OR-5 L18 Social Networking, ImpactL19 Revision

L18 To apply the information available in various resources to develop a BI systemL19 To clear doubts


SPILL OVERWeek 7 Lecture 20 Spill Over

Week 7 Lecture 21 Spill Over

MID-TERMSPILL OVER

Week 7 Lecture 20 Spill OverLecture 21 Spill Over

Week 8 Lecture 22 Spill OverLecture 23 Spill OverLecture 24 Spill Over

Scheme for CA:Component Frequency Out Of Each Marks Total MarksHomework,Test 2 2 15 30Class presentation 1 1 5 5

Total :- 20 35

Details of Academic Task(s)AT No. Objective Topic of the Academic Task Nature of Academic Task

(group/individuals/field work

Evaluation Mode Allottment / submission Week

HW1 To enable learning of students through Experiental method

There are plenty of Exercises given at the end of each chapter in the textbook. Most of these are experiential, some are web based where students are mostly required to perform an activity or analyze something and present it in a written form. The students will be given these Chapter ending tasks in groups of 2 to 4 depending on the size of the class

Group Written report: Introduction - 5 Marks, Objectives - 5 marks, Methodology - 10 marks, Result and conclusion - 10 marks, total 30 marks (scaled down to 15)

1 / 6

Test1 To ensure that students are thorough with the concepts

Quiz to be taken from Chapters covered up to 3rd week Individual 4 questions of 10 marks each and 1 question of 5 marks would be given (total 45 marks, scaled down to 15)

2 / 4

Class presentation1 To enhance the communication skills of students

Topic should be related to the course. Individual 15 marks for 5 minutes presentation. Scaled down to 5 marks.

1 / 6

List of suggested topics for term paper[at least 15] (Student to spend about 15 hrs on any one specified term paper)

Sr. No. Topic1 Changes made....

ip business intelligence

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