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2014 pearson education inc biology

18/10/2021 Client: muhammad11 Deadline: 2 Day

Business_Intelligence

Discussion :

Carefully review and use either of the book options below as a reference for various aspects of analytics.

Sharda, R., Delen, D., & Turban, E. (2015) Business intelligence and analytics: Systems for decision support (10th ed.). Boston: Pearson. Print: ISBN-13: 978-0-13-305090-5
Sharda, R., Delen, D., & Turban, E. (2020) Analytics, data science, & artificial intelligence: Systems for decision support (11th ed.). Boston: Pearson. Print: ISBN-13: 978-0-13-519201-6
Important Note: All students are welcome to use outside research in aspects of analytics.
After reading and analyzing content from book references and or from outside research, select “one” of the research options below and respond.

Go to www.IBM.com and find at least three customer case studies on Big Data and write a report where you discuss the commonalities and differences of these cases.
Go to www.cloudera.com and find at least three customer case studies on Hadoop implementation, and write a report where you discuss the commonalities and differences of these cases.
Go to www.google.com/scholar, and search for articles on stream analytics. Find at least three related articles. Read and summarize your findings.
Go to www.google.com/scholar, and search for articles on data stream mining. Find at least three related articles. Read and summarize your findings.
Go to www.google.com/scholar, and search for articles that talk about Big Data versus data warehousing. Find at least five articles. Read and summarize your findings.
Discussion Expectations

Please make sure to proofread your post prior to submission. They should be well written and free of grammatical or typographical errors.

Knowledge and skills paper:

Graded Assignment: Knowledge and Skills Paper

Paper Section 1: Reflection and Literature Review

Using Microsoft Word and Professional APA format, prepare a professional written paper supported with three sources of research that details what you have learned from chapters 7, 8, 9, and 10. This section of the paper should be a minimum of two pages.

Paper Section 2: Applied Learning Exercises

In this section of the professional paper, apply what you have learned from chapters 7, 8, 9, and 10 to descriptively address and answer the problems below. Important Note: Dot not type the actual written problems within the paper itself.

Survey and compare and possibly test some text mining tools and vendors. Start with clearforest.com and megaputer.com. Also consult with dmreview.com to further identify some text mining products to explore and even test?
Survey and compare and possibly test some Web mining tools and vendors. Identify some Web mining products and service providers that could potentially be useful in a work environment you may want to be part of.
Investigate via a Web search how models and their solutions are used by the U.S. Department of Homeland Security in the “war against terrorism.” Also investigate how other governments or government agencies are using models in their missions.
Search online to find vendors of genetic algorithms and investigate the business applications of their products and even possibly test them where applicable. What kinds of applications are most prevalent and why?
Important Note: With limited time for a college class, perfection is not expected but effort to be exposed to various tools with attempts to learn about them is critical when considering a career in information technology associated disciplines.
Important Note: There is no specific page requirement for this section of the paper but make sure any content provided fully addresses each problem.

Paper Section 3: Conclusions

After addressing the problems, conclude your paper with details on how you will use this knowledge and skills to support your professional and or academic goals. This section of the paper should be around one page including a custom and original process flow or flow diagram to visually represent how you will apply this knowledge going forward. This customized and original flow process flow or flow diagram can be created using the “Smart Art” tools in Microsoft Word.

Paper Section 4: APA Reference Page

The three or more sources of research used to support this overall paper should be included in proper APA format in the final section of the paper.

Paper Review and Preparation to submit for Grading

Please make sure to proof read your post prior to submission. This professional paper should be well written and free of grammatical or typographical errors. Also remember not to plagiarize!!!!!!!!!!!!

Important Reminder: Assessment of discussion boards and other writing assignments account for 75% of overall grading and below are how grades will be assessed for this assignment:

Chapter 10:

Modeling and Analysis: Heuristic Search Methods and Simulation

Business Intelligence and Analytics: Systems for Decision Support

(10th Edition)

Business Intelligence and Analytics: Systems for Decision Support

(10th Edition)

10-‹#›

Learning Objectives

Explain the basic concepts of simulation and heuristics, and when to use them

Understand how search methods are used to solve some decision support models

Know the concepts behind and applications of genetic algorithms

Explain the differences among algorithms, blind search, and heuristics

(Continued…)

10-‹#›

Learning Objectives

Understand the concepts and applications of different types of simulation

Explain what is meant by system dynamics, agent-based modeling, Monte Carlo, and discrete event simulation

Describe the key issues of model management

10-‹#›

Opening Vignette

System Dynamics Allows Fluor

Corporation to Better Plan for Project and Change Management

Background

Problem description

Proposed solution

Results

Answer & discuss the case questions...

10-‹#›

Questions for the Opening Vignette

Explain the use of system dynamics as a simulation tool for solving complex problems.

In what ways was it applied in Fluor Corporation to solve complex problems?

How does a what-if analysis help a decision maker to save on cost?

In your own words, explain the factors that might have triggered the use of system dynamics to solve change management problems in Fluor Corporation…

10-‹#›

Problem-Solving Search Methods

Search: choice phase of decision making

Search is the process of identifying the best possible solution / course of action [under limitations such as time, …]

Search techniques include

analytical techniques,

algorithms,

blind searching, and

heuristic searching

10-‹#›

Problem-Solving Search Methods

10-‹#›

Problem-Solving Search Methods - Algorithmic/Heuristic

Cuts the search space

Gets satisfactory solutions more quickly and less expensively

Finds good enough feasible solutions to complex problems

Heuristics can be

Quantitative

Qualitative (in ES)

Traveling Salesman Problem see the example next >>>

10-‹#›

Traveling Salesman Problem

What is it?

A traveling salesman must visit customers in several cities, visiting each city only once, across the country. Goal: Find the shortest possible route.

Total number of unique routes (TNUR):

TNUR = (1/2) (Number of Cities – 1)!

Number of Cities TNUR

5 12

6 60

9 20,160

20 1.22 1018

10-‹#›

Traveling Salesman Problem

10-‹#›

Traveling Salesman Problem

Rule 1: Starting from home base, go to the closest city

Rule 2: Always follow an exterior route

10-‹#›

Application Case 10.1

Chilean Government Uses Heuristics to Make Decisions on School Lunch Providers

Questions for Discussion

What were the main challenges faced by JUNAEB?

What operation research methodologies were employed in achieving homogeneity across territorial units?

What other approaches could you use in this case study?

10-‹#›

When to Use Heuristics

When to Use Heuristics?

Inexact or limited input data

Complex reality

Reliable, exact algorithm not available

Computation time excessive

For making quick decisions

Limitations of Heuristics!

Cannot guarantee an optimal solution

10-‹#›

Tabu search

Intelligent search algorithm

Genetic algorithms

Survival of the fittest

Simulated annealing

Analogy to Thermodynamics

Ant colony and other Meta-heuristics

Modern Heuristic Methods

10-‹#›

Genetic Algorithms

It is a popular heuristic search technique

Mimics the biological process of evolution

Genetic algorithms

Software programs that “learn/search” in evolutionary manner, similar to the way biological systems evolve

An efficient, domain-independent search heuristic for a broad spectrum of problem domains

Main theme: Survival of the fittest

Moving toward better and better solutions by letting only the fittest parents create the future generations

10-‹#›

Evolutionary Algorithm

10010110

01100010

10100100

10011001

01111101

. . .

10010110

01100010

10100100

10011101

01111001

. . .

Selection

Reproduction

. Crossover

. Mutation

Current

generation

Elitism

10-‹#›

Each candidate solution is called a chromosome

A chromosome is a string of genes

Chromosomes can copy themselves, mate, and mutate via evolution

In GA we use specific genetic operators

Reproduction

Crossover

Mutation

GA Structure and GA Operators

10-‹#›

Genetic Algorithms - Example: The Vector Game

Description of the Vector Game

Identifying a string of 5 binary digits

Default Strategy: Random Trial and Error

Improved Strategy: Use of Genetic Algorithms

In an iterative fashion, using genetic algorithm process and genetic operators, find the opponent’s digit sequence

See your book for functional details

10-‹#›

Item: 1 2 3 4 5 6 7

Benefit: 5 8 3 2 7 9 4

Weight: 7 8 4 10 4 6 4

Knapsack holds a maximum of 22 pounds

Need to fill it for maximum benefit (one per item)

Solutions take the form of a string of 1’s

Example Solution: 1 1 0 0 1 0 0

Means choose items 1, 2, 5:

Weight = 21, Benefit = 20

Evolver solution works in Microsoft Excel… 

A Classic GA Example: The Knapsack Problem

10-‹#›

Define the objective function and constraint(s)

10-‹#›

Identify the decision variables and their characteristics

10-‹#›

Observe and analyze the results

10-‹#›

Observe and analyze the results

10-‹#›

The Knapsack Problem at Evolver

Monitoring the solution generation process…

10-‹#›

Genetic Algorithms

Limitations of Genetic Algorithms

Does not guarantee an optimal solution (often settles in a sub optimal solution / local minimum)

Not all problems can be put into GA formulation

Development and interpretation of GA solutions requires both programming and statistical skills

Relies heavily on the random number generators

Locating good variables for a particular problem and obtaining the data for the variables is difficult

Selecting methods by which to evolve the system requires experimentation and experience

10-‹#›

Genetic Algorithm Applications

Dynamic process control

Optimization of induction rules

Discovery of new connectivity topologies (NNs)

Simulation of biological models of behavior

Complex design of engineering structures

Pattern recognition

Scheduling, transportation, and routing

Layout and circuit design

Telecommunication, graph-based problems, …

10-‹#›

Simulation

Simulation is the “appearance” of reality

It is often used to conduct what-if analysis on the model of the actual system

It is a popular DSS technique for conducting experiments with a computer on a comprehensive model of the system to assess its dynamic behavior

Often used when the system is too complex for other DSS techniques

10-‹#›

Application Case 10.3

Simulating Effects of Hepatitis B Interventions

Questions for Discussion

Explain the advantage of operations research methods such as simulation over clinical trial methods in determining the best control measure for Hepatitis B.

In what ways do the decision and Markov models provide cost-effective ways of combating the disease?

Discuss how multidisciplinary background is an asset in finding a solution for the problem described in the case.

Besides healthcare, in what other domain could such a modeling approach help reduce cost?

10-‹#›

Imitates reality and captures its richness both in shape and behavior

“Represent” versus “Imitate”

Technique for conducting experiments

Descriptive, not normative tool

Often to “solve” [i.e., analyze] very complex systems/problems

Simulation should be used only when a numerical optimization is not possible

Major Characteristics of Simulation

10-‹#›

Advantages of Simulation

The theory is fairly straightforward

Great deal of time compression

Experiment with different alternatives

The model reflects manager’s perspective

Can handle wide variety of problem types

Can include the real complexities of problems

Produces important performance measures

Often it is the only DSS modeling tool for non-structured problems

10-‹#›

Disadvantages of Simulation

Cannot guarantee an optimal solution

Slow and costly construction process

Cannot transfer solutions and inferences to solve other problems (problem specific)

So easy to explain/sell to managers, may lead to overlooking analytical solutions

Software may require special skills

10-‹#›

Simulation Methodology

Steps:

1. Define problem 5. Conduct experiments

2. Construct the model 6. Evaluate results

3. Test and validate model 7. Implement solution

4. Design experiments

10-‹#›

Simulation Types

Probabilistic/Stochastic vs. Deterministic Simulation

Uses probability distributions

Time-dependent vs. Time-independent Simulation

Monte Carlo technique (X = A + B) [A, B, and X are all distributions]

Discrete Event vs. Continuous Simulation

Simulation Implementation

Visual Simulation and/or Object-Oriented Simulation

10-‹#›

Visual interactive modeling (VIM), also called Visual Interactive Simulation or Visual interactive problem solving

Uses computer graphics to present the impact of different management decisions

Often integrated with 3G and GIS

Users can perform sensitivity analysis

Static or dynamic (animation) systems

Virtual reality, immersive, …

Visual Interactive Simulation (VIS)

10-‹#›

Traffic at an Intersection from the Orca Visual Simulation

10-‹#›

Application Case 10.4

Improving Job-Shop Scheduling Decisions Through RFID: A Simulation-Based Assessment

Background

Problem description

Proposed solution

Results

10-‹#›

SIMIO Simulation Software

10-‹#›

SIMIO Simulation Software

10-‹#›

SIMIO Simulation Software

10-‹#›

Simulation Software

A comprehensive list can be found at

orms-today.org/surveys/Simulation/Simulation.html

Simio LLC, simio.com

SAS Simulation, sas.com

Lumina Decision Systems, lumina.com

Oracle Crystal Ball, oracle.com

Palisade Corp., palisade.com

Rockwell Intl., arenasimulation.com …

10-‹#›

System Dynamics Modeling

Macro-level simulation models in which aggregate values and trends are considered

Objective is to study the overall behavior of a system over time as a whole

Evolution of the various components of the system over time and as a result of interplay between the components over time

First introduced by Forrester (1958)

A widely used technique in operations research and management science

10-‹#›

System Dynamics Modeling

10-‹#›

Agent-Based Modeling

Agent - an autonomous computer program that observes and acts on an environment and directs its activity toward achieving specific goals

Relatively new technology

Other names include

Software agents

Wizards

Knowbots, Both

Intelligent software robots (Softbots) …

10-‹#›

Agent-Based Modeling

Agent-based modeling (ABM) is a simulation modeling technique to support complex decision systems where a system is modeled as a set of autonomous decision-making units called agents

A bottom-up approach to simulation modeling

Agent-based modeling platforms

SWARM (www.swarms.org),

Netlogo (http://ccl.northwestern.edu/netlogo),

RePast/Sugarscape (www.repast.sourceforge.net),

…

10-‹#›

Application Case 10.5

Agent-Based Simulation Helps Analyze Spread of a Pandemic Outbreak

Questions for Discussion

What are the characteristics of an agent-based simulation model?

List the various factors that were fed into the agent-based simulation model described in the case.

Elaborate on the benefits of using agent-based simulation models.

Besides disease prevention, in which other situations could agent-based simulation be employed?

10-‹#›

End of the Chapter

Questions, comments

10-‹#›

All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted, in any form or by any means, electronic, mechanical, photocopying, recording, or otherwise, without the prior written permission of the publisher. Printed in the United States of America.

10-‹#›

Start

Represent problem’s

chromosome structure

Generate initial solutions

(the initial generation)

Select elite solutions; carry

them into next generation

Test:

Is the solution

satisfactory?

Stop-

Deploy the

solution

Select parents to reproduce;

apply crossover and mutation

generation

of solutions

Offspring

Elites

Yes

Staff time saved

E-Rx

E-Note

adverse drug

event (ADE)

ADE correction

cost

patient

treatment time

medical records

storage

radiology

performance

laboratory

performance

staff training

compliance via

EHR

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