IE4425 FINAL EXAM REVIEW
Review Guide Overview
The final exam is comprehensive, covering all lecture/lab materials since start of term. This guide only covers topics
since the midterm, however, so it is suggested you also do a quick review of the midterm exam review guide and
midterm exam solutions. Although comprehensive, more coverage will be given on the exam to topics since the
midterm.
Topics covered this semester include:
Business Organization, Processes & ERP Systems Concepts
Information Systems Overview
Requirements Definition
Data collection; defining/refining/documenting; alternatives Identification & vended vs. develop decisions.
Documenting: Use Case Diagrams & Descriptions, interface prototypes, navigation maps
Data Modeling & Design
Objectives, Stages, Types
Entity-Relational (ER) Model:
o Basic Relational Principles – Entities, Attributes, Relations & Joins, Keys, Indexes, ...
o Conceptual ERD, Physical ERD, UML Database Notation Diagrams – constructing, interpreting
o Normalization (1NF, 2NF, 3NF) – performing, evaluating
o Internal Data Model Design – detailed design of tables and their fields, indexes, relationships, and other data
integrity constraints (domain); consideration of regulatory/audit/compliance and history requirements; data
dictionary
o External design – short answer, m/c type questions only
o Physical Database Design – concepts, short answer, m/c type questions only
o SQL query language: be able to write and interpret any SELECT or DML query, be able to interpret DDL queries
& SQL programs:
SELECT queries: SELECT clause, INTO clause, FROM clause (including joins), WHERE clause, GROUP BY,
HAVING, ORDER BY, transforms (aka pivot or crosstab), unions, aggregate functions, other functions,
calculated expressions, subqueries, parameter queries
DML (Action) queries – insert, update, delete
Basic DDL queries – CREATE TABLE, ALTER TABLE, DROP TABLE
Data in transit models (CSV, JSON, XML) – be able to construct / interpret
OLAP & MD Data models – ETL, data-warehouses/ data-marts, cubes/star schema design, measures, dimensions,
aggregates, PivotTable. Be able to construct / interpret
NoSQL models – be able to select an appropriate model
Process Modeling
Workflow/BPM concepts, interpret BPMN diagrams
Interface Modeling & Design
User Interfaces (UI) design concepts, Navigation systems, Usability testing
BI
Concepts, KPIs, Tableau concepts
Analytics
Preprocessing methods
Feature selection methods
Machine learning approaches: Association Rule Mining, Clustering, Classification, Regression
Training & Testing (supervised learning techniques)
Performance Metrics: Accuracy, Precision, Recall, F1, R, R 2, interpreting results & significance
Python as relates to the above approaches and working with dataframes. You may be asked to select which code is
correct, interpret what code does, or write a line or two of code to solve a stated problem.
1
,Review Questions
This guide represents a composite of questions from many different past exams.
Not every topic in the topic list above is represented in a sample question within the guide. This does not mean it will
not appear on the test! If the topic area is listed above, it is fair game.
With larger class sizes and reduced TA support in recent years, I have moved more towards multiple choice and T/F type
questions. You are likely to see more multiple-choice and T/F questions than you see in the review guide here, as was
the case on your midterm exam.
Some but not all problems in the guide have solutions; I will be happy to provide some hints if you have a question on a
problem AFTER you've made a good effort at solving it yourself (I will not, however, provide solutions).
It is not my intention that you work every problem in the guide. Do a quick pass
through the guide to check which problems you have a fair idea how to answer
and which you do not, and then spend time reviewing the latter problems.
Questions are presented here by topic area; questions will not be in topic order on the exam.
2
, Business Processes & ERP
(See Midterm Review Guide)
Information Systems Overview
(See Midterm Review Guide)
IS Development Lifecycle & Systems Analysis / Requirements Definition
(See Midterm Review Guide. Additional problems on use cases and alternatives are included here)
1. [10pts] Consider an information system that would use the exam handout ERD in Figure 10 and identify the
likely use cases for the ERD. Be as complete as you can. For each use case, identify the table(s) that would
be used by the use case.
SOLUTION:
While your list didn't need to be completely comprehensive, it did need to
identify both customer-facing and back-office use cases. Here is a
representative set (you can come up with many more)
Customer facing:
Catalog Search (title, category, publishers)
Checkout (title, customer, order, orderdetail)
Manage account info (customer)
Manage orders (customer, order, orderdetail, titles, publishers,
categories)
Back office:
Manage Catalog – CRUD (create, read, update, delete) title (title,
category, publishers)
Manage Publishers – CRUD (publishers)
Manage Categories – CRUD (categories)
Manage Orders – CRUD (same as checkout)
Manage Customers – CRUD (customer)
2. [7pts] How does the requirements definition process differ if looking at existing software applications as
opposed to developing an application from scratch?
When selecting from existing software applications, requirements definition
generally is more limited, and generally consists of identifying high-level
features required and possibly providing overviews of business processes so
that vendors can show how their software supports it. Most of the work is
in assessing how well the vendors' implementations meet the company's needs.
When developing the application from scratch, details must be specified as
to how forms and reports will look and work.
3
Review Guide Overview
The final exam is comprehensive, covering all lecture/lab materials since start of term. This guide only covers topics
since the midterm, however, so it is suggested you also do a quick review of the midterm exam review guide and
midterm exam solutions. Although comprehensive, more coverage will be given on the exam to topics since the
midterm.
Topics covered this semester include:
Business Organization, Processes & ERP Systems Concepts
Information Systems Overview
Requirements Definition
Data collection; defining/refining/documenting; alternatives Identification & vended vs. develop decisions.
Documenting: Use Case Diagrams & Descriptions, interface prototypes, navigation maps
Data Modeling & Design
Objectives, Stages, Types
Entity-Relational (ER) Model:
o Basic Relational Principles – Entities, Attributes, Relations & Joins, Keys, Indexes, ...
o Conceptual ERD, Physical ERD, UML Database Notation Diagrams – constructing, interpreting
o Normalization (1NF, 2NF, 3NF) – performing, evaluating
o Internal Data Model Design – detailed design of tables and their fields, indexes, relationships, and other data
integrity constraints (domain); consideration of regulatory/audit/compliance and history requirements; data
dictionary
o External design – short answer, m/c type questions only
o Physical Database Design – concepts, short answer, m/c type questions only
o SQL query language: be able to write and interpret any SELECT or DML query, be able to interpret DDL queries
& SQL programs:
SELECT queries: SELECT clause, INTO clause, FROM clause (including joins), WHERE clause, GROUP BY,
HAVING, ORDER BY, transforms (aka pivot or crosstab), unions, aggregate functions, other functions,
calculated expressions, subqueries, parameter queries
DML (Action) queries – insert, update, delete
Basic DDL queries – CREATE TABLE, ALTER TABLE, DROP TABLE
Data in transit models (CSV, JSON, XML) – be able to construct / interpret
OLAP & MD Data models – ETL, data-warehouses/ data-marts, cubes/star schema design, measures, dimensions,
aggregates, PivotTable. Be able to construct / interpret
NoSQL models – be able to select an appropriate model
Process Modeling
Workflow/BPM concepts, interpret BPMN diagrams
Interface Modeling & Design
User Interfaces (UI) design concepts, Navigation systems, Usability testing
BI
Concepts, KPIs, Tableau concepts
Analytics
Preprocessing methods
Feature selection methods
Machine learning approaches: Association Rule Mining, Clustering, Classification, Regression
Training & Testing (supervised learning techniques)
Performance Metrics: Accuracy, Precision, Recall, F1, R, R 2, interpreting results & significance
Python as relates to the above approaches and working with dataframes. You may be asked to select which code is
correct, interpret what code does, or write a line or two of code to solve a stated problem.
1
,Review Questions
This guide represents a composite of questions from many different past exams.
Not every topic in the topic list above is represented in a sample question within the guide. This does not mean it will
not appear on the test! If the topic area is listed above, it is fair game.
With larger class sizes and reduced TA support in recent years, I have moved more towards multiple choice and T/F type
questions. You are likely to see more multiple-choice and T/F questions than you see in the review guide here, as was
the case on your midterm exam.
Some but not all problems in the guide have solutions; I will be happy to provide some hints if you have a question on a
problem AFTER you've made a good effort at solving it yourself (I will not, however, provide solutions).
It is not my intention that you work every problem in the guide. Do a quick pass
through the guide to check which problems you have a fair idea how to answer
and which you do not, and then spend time reviewing the latter problems.
Questions are presented here by topic area; questions will not be in topic order on the exam.
2
, Business Processes & ERP
(See Midterm Review Guide)
Information Systems Overview
(See Midterm Review Guide)
IS Development Lifecycle & Systems Analysis / Requirements Definition
(See Midterm Review Guide. Additional problems on use cases and alternatives are included here)
1. [10pts] Consider an information system that would use the exam handout ERD in Figure 10 and identify the
likely use cases for the ERD. Be as complete as you can. For each use case, identify the table(s) that would
be used by the use case.
SOLUTION:
While your list didn't need to be completely comprehensive, it did need to
identify both customer-facing and back-office use cases. Here is a
representative set (you can come up with many more)
Customer facing:
Catalog Search (title, category, publishers)
Checkout (title, customer, order, orderdetail)
Manage account info (customer)
Manage orders (customer, order, orderdetail, titles, publishers,
categories)
Back office:
Manage Catalog – CRUD (create, read, update, delete) title (title,
category, publishers)
Manage Publishers – CRUD (publishers)
Manage Categories – CRUD (categories)
Manage Orders – CRUD (same as checkout)
Manage Customers – CRUD (customer)
2. [7pts] How does the requirements definition process differ if looking at existing software applications as
opposed to developing an application from scratch?
When selecting from existing software applications, requirements definition
generally is more limited, and generally consists of identifying high-level
features required and possibly providing overviews of business processes so
that vendors can show how their software supports it. Most of the work is
in assessing how well the vendors' implementations meet the company's needs.
When developing the application from scratch, details must be specified as
to how forms and reports will look and work.
3
