Enterprise Information Systems
Chapter Exam Questions
Course Introduction
Enterprise Information Systems explores the architecture, implementation, and management of large-scale information systems that support business processes and operations within organizations. The course covers topics such as Enterprise Resource Planning (ERP), Customer Relationship Management (CRM), Supply Chain Management (SCM), and Business Intelligence (BI) systems. Students learn how these integrated systems facilitate real-time data sharing, streamline workflows, and enable informed decision-making across various organizational departments. Through case studies and practical exercises, students examine the selection, customization, and challenges of deploying enterprise-level IT solutions to achieve strategic business goals.
Recommended Textbook
Business Intelligence A Managerial Perspective on Analytics 3rd Edition by Ramesh Sharda
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Chapter 1: An Overview of Business Intelligence, Analytics, and Decision Support
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Sample Questions
Q1) Prescriptive BI capabilities are viewed as more powerful than predictive ones for all the following reasons EXCEPT
A) prescriptive BI gives actual guidance as to actions.
B) understanding the likelihood of certain events often leaves unclear remedies.
C) only prescriptive BI capabilities have monetary value to top-level managers.
D) prescriptive models generally build on (with some overlap) predictive ones.
Answer: C
Q2) Computerized support is only used for organizational decisions that are responses to external pressures,not for taking advantage of opportunities.
A)True
B)False
Answer: False
Q3) Traditional BI systems use a large volume of static data that has been extracted,cleansed,and loaded into a data warehouse to produce reports and analyses.
A)True
B)False
Answer: True
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Chapter 2: Data Warehousing
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Q1) Performing extensive ________ to move data to the data warehouse may be a sign of poorly managed data and a fundamental lack of a coherent data management strategy.
Answer: extraction,transformation,and load (ETL)
Q2) In which stage of extraction,transformation,and load (ETL)into a data warehouse are data aggregated?
A) transformation
B) extraction
C) load
D) cleanse
Answer: A
Q3) What is the definition of a data warehouse (DW)in simple terms?
Answer: In simple terms,a data warehouse (DW)is a pool of data produced to support decision making; it is also a repository of current and historical data of potential interest to managers throughout the organization.
Q4) In the Michigan State Agencies case,the approach used was a(n)________ one,instead of developing separate BI/DW platforms for each business area or state agency.
Answer: enterprise
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Chapter 3: Business Reporting, visual Analytics, and Business Performance Management
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Sample Questions
Q1) ________ management reports are used to manage business performance through outcome-oriented metrics in many organizations.
Answer: Metric
Q2) What are the basic ingredients of a good collection of performance measures?
Answer: .Measures should focus on key factors.
.Measures should be a mix of past,present,and future.
.Measures should balance the needs of shareholders,employees,partners,suppliers,and other stakeholders.
.Measures should start at the top and flow down to the bottom.
.Measures need to have targets that are based on research and reality rather than be arbitrary.
Q3) The dashboard for the WebFOCUS BI platform in the Travel and Transport case study required client side software to operate.
A)True
B)False
Answer: False
Q4) A strategically aligned metric is also known as a key ________.
Answer: performance indicator
5
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Chapter 4: Data Mining
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Sample Questions
Q1) Statistics and data mining both look for data sets that are as large as possible.
A)True
B)False
Q2) Using data mining on data about imports and exports can help to detect tax avoidance and money laundering.
A)True
B)False
Q3) Which data mining process/methodology is thought to be the most comprehensive,according to kdnuggets.com rankings?
A) SEMMA
B) proprietary organizational methodologies
C) KDD Process
D) CRISP-DM
Q4) The data field "ethnic group" can be best described as
A) nominal data.
B) interval data.
C) ordinal data.
D) ratio data.
Q5) Describe <b>cluster analysis</b> and some of its applications.
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Chapter 5: Text,web,and Social Analytics
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Q1) Categorization and clustering of documents during text mining differ only in the preselection of categories.
A)True
B)False
Q2) When viewed as a binary feature,________ classification is the binary classification task of labeling an opinionated document as expressing either an overall positive or an overall negative opinion.
Q3) Web site visitors who critique and create content are more engaged than those who join networks and spectate.
A)True
B)False
Q4) A(n)________ is one or more Web pages that provide a collection of links to authoritative Web pages.
Q5) Why are the users' page views and time spent on your Web site important metrics?
Q6) Describe the query-specific clustering method as it relates to clustering.
Q7) ________,also called homonyms,are syntactically identical words with different meanings.
Q8) What is the difference between white hat and black hat SEO activities?
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Q9) Web ________ are used to automatically read through the contents of Web sites.
Chapter 6: Big Data and Analytics
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Q1) When considering Big Data projects and architecture,list and describe five challenges designers should be mindful of in order to make the journey to analytics competency less stressful.
Q2) Most Big Data is generated automatically by ________.
Q3) Despite their potential,many current NoSQL tools lack mature management and monitoring tools.
A)True
B)False
Q4) The Big Data and Analysis in Politics case study makes it clear that the unpredictability of elections makes politics an unsuitable arena for Big Data.
A)True
B)False
Q5) There is a current undersupply of data scientists for the Big Data market.
A)True
B)False
Q6) It is important for Big Data and self-service business intelligence go hand in hand to get maximum value from analytics.
A)True
B)False
Page 8
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Chapter 7: Business Analytics: Emerging Trends and Future
Directions
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Q1) From massive amounts of high-dimensional location data,algorithms that reduce the dimensionality of the data can be used to uncover trends,meaning,and relationships to eventually produce human-understandable representations.
A)True
B)False
Q2) In what ways can communications companies use geospatial analysis to harness their data effectively?
Q3) Data-as-a-service began with the notion that data quality could happen in a centralized place,cleansing and enriching data and offering it to different systems,applications,or users,irrespective of where they were in the organization,computers,or on the network.
A)True
B)False
Q4) How does Oklahoma Gas and Electric use the Teradata platform to manage the electric grid?
Q5) Location information from ________ phones can be used to create profiles of user behavior and movement.
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Q6) When an organization-wide,major restructuring is needed,the process is referred to as ________.