
Introductory Relational Database Design for Business, with Microsoft Access
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Preface ix
1 Basic Definitions and Concepts 1
Basic Terms and Definitions 1
Types of Information Systems 3
2 Beginning Fundamentals of Relational Databases and MS Access 7
Beginning Fundamentals of MS Access 8
A "Hands-On" Example 9
Introduction to Forms 15
Another Method to Create Forms 18
Introduction to Reports 22
Introduction to Queries 26
Common Datatypes in MS Access 32
Exercises 34
3 Introduction to Data Management and Database Design 43
Introduction to Data Management 43
General Data Management Issues 43
Classifying Information Systems Tasks: Transaction and Analytical Processing 45
What is Wrong with Just One Table? 46
Repeating Groups 47
An Illustration of Multiple Tables and Foreign Keys 48
4 Basic Relational Database Theory 53
Tables and Their Characteristics 53
Primary Keys and Composite Keys 55
Foreign Keys and Outline Notation 57
Creating Entity-Relationship (ER) Diagrams 59
Functional Dependency 60
Dependency Diagrams 61
Partial Dependency 62
Transitive Dependency 63
Database Anomalies 63
What Causes Anomalies? 64
How to Fix Anomalies 65
Good Database Design Principles 66
Normalization and Zip Codes 67
Expanding the Customer Loans Database 68
DVD Lending Library Example without Loan History 71
The DVD Lending Library Example with Loan History 75
Subtypes 78
Exercises 85
5 Multiple Tables in Access 95
The Relationships Window and Referential Integrity 95
Nested Table View 100
Nested Forms 101
Queries with Multiple Tables 103
Multiple Joins and Aggregation 108
Personnel: Database Design with Multiple Paths between Tables 115
Creating the Database in Access using Autonumber Keys 119
A Simple Query and a Different Way to Express Joins in SQL 120
Exercises 123
6 More about Forms and Navigation 127
More Capabilities of Forms 127
Packaging it Up - Navigation 132
Exercises 135
7 Many-to-Many Relationships 139
Focus Groups Example 139
The Plumbing Store: Many-to-Many with an Additional Quantity Field 143
Hands- On Exercise and More About Queries and SQL 146
Project Teams: Many-to-Many with "Flavors" of Membership 154
The Library 159
Exercises 163
8 Multiple Relationships between the Same Pair of Tables 171
Commuter Airline Example 171
The College 177
Sports League Example 181
Multiple Relationships in Access 183
Exercises 184
9 Normalization 189
First Normal Form 189
Second Normal Form 192
Third Normal Form 194
More Normal Forms 197
Key Factors to Recognize 3NF 198
Example with Multiple Candidate Keys 198
Normalizing an Office Supplies Database 198
Summary of Guidelines for Database Design 202
Exercises 203
10 Basic Structured Query Language (SQL) 215
Using SQL in Access 215
The SELECT ... FROM Statement 215
WHERE Conditions 217
Inner Joins 218
Cartesian Joins and a Different Way to Express Inner Joins 221
Aggregation 228
GROUP BY 231
HAVING 237
ORDER BY 238
The Overall Conceptual Structure of Queries 240
Exercises 243
11 Advanced Query Techniques 253
Outer Joins 253
Outer Joins and Aggregation 256
Joining Multiple Records from the Same Table: AS in the FROM Clause 260
Another Use for AS in the FROM Clause 262
An Introduction to Query Chaining and Nesting 262
A More Complicated Example of Query Chaining: The League Standings 265
Subqueries and Back to the Plumbing Store Database 270
Practical Considerations and "Bending the Rules" Against Redundancy 274
Exercises 275
12 Unary Relationships 279
Employee Database 279
Setting Up and Querying a Unary Relationship in Access 283
The Course Catalog Database 291
Exercises 294
Further Reading 301
Index 303
1
Basic Definitions and Concepts
This chapter covers the following topics:
- Basic definitions and concepts in database technology
- The role of computers and network technology in helping run businesses and other organizations
- Common types of information processing systems in current use
Basic Terms and Definitions
There are some basic definitions and concepts that should provide useful context for understanding database design. Some of the terms we define are in common use but take on specific meaning in the information technology field.
Datum is a singular word, and data is its plural. A datum (sometimes called a "data item") is a "particle" of information like "12" or "Q."
Information refers to data that are structured and organized to be useful in making a decision or performing some task. Relational databases are currently the most common way data are organized into information; hence this book's focus on relational databases.
Knowledge denotes understanding or evaluating information. An example could be when Casleton Corporation analyzes its recruiting data and concludes that recruits from Driftwood College tend to have good performance evaluations only if their GPAs are at least 3.0. Based on this "knowledge," Casleton's managers might choose to screen applicants from Driftwood College by their GPAs, interviewing only those graduates with at least a 3.0 GPA.
For this book, we will focus on representing information within computer systems. Note, however, that knowledge can also be represented within computers. One common kind of knowledge representation (KR) within computers is part of the field of artificial intelligence (AI). One common business application of AI in business is in automated business rules systems. Another recently popularized AI application is the "Siri" personal assistant on iPhones and iPads, or the similar "Google Voice" app on Android devices. Although its business uses are substantial and gradually expanding, we will not discuss AI, as relational database systems are simpler and far more ubiquitous.
Information systems consist of the ways that organizations store, move, organize, and manipulate/process their information. The components that implement information systems - in other words, information technology - consist of the following:
- Hardware - physical tools: computer and network hardware, but also low-tech objects such as pens and paper
- Software - (changeable) instructions for the hardware (when applicable; the simplest hardware does not need software)
- People
- Procedures - instructions for people
- Data/databases
Information systems existed before computers and networks - they just used relatively simple hardware that usually did not need software (at least as we know it today). For example, filing all sales receipts alphabetically by customer in a filing cabinet is a form of information system, although it is not electronic. Tax records kept on clay tablets by ancient civilizations were also a form of information system. Strictly speaking, this book is about an aspect of CBISs (computer-based information systems). Because of the present ubiquity of computers in information systems, we usually leave out the "CB," treating it as implicit.
Present-day CBISs have the following advantages over older, manual information systems:
- They can perform numerical computations and other data processing much more quickly, accurately, and cheaply than people.
- They can communicate very quickly and accurately.
- They can store large amounts of information quickly and cheaply, and information retrieval can often be very rapid.
- They can, to varying degrees, automate tasks and processes that previously required human labor.
- Information no longer needs to be "stuck" with particular things, locations, or people.
However, increasingly, automated systems can have drawbacks, such as the following:
- Small errors can have a much wider impact than in a less automated system. For example, in March 2003, a minor software bug in some airport data collection code - which programmers were aware of but considered too small to cause operational problems - grounded all aircraft in Japan for two days.
- Fewer people in the organization understand exactly how information is processed.
- Sometimes, malfunctions may go unnoticed. For example, American Airlines once discovered a serious bug in its "yield management" software only after reporting quarterly results that were significantly lower than expected. ("Yield management" refers to the process of deciding how many aircraft seats to make available for sale at different fare levels.)
Information architecture is the particular way an organization has arranged its information systems: for example, a particular network of computers running particular software might support a firm's marketing organization, while another network of computers running different software might support its production facilities, and so forth.
Information infrastructure consists of the hardware and software that support an organization's information architecture, together with the personnel and services dedicated primarily to maintaining and developing that hardware and software.
Application and application program (nowadays sometimes simply "app") are somewhat ill-defined terms but typically denote computer software and databases supporting a particular task or group of tasks. For example, a firm's human resource department might use one application to analyze benefit costs and usage, and another to monitor employee turnover.
A classic business IT problem is that applications, especially those used by different parts of an organization, may not communicate with one another effectively - for example, a new hire or retirement might have to be separately entered into both of the human resources systems described above because they do not communicate or share a common database.
Types of Information Systems
Particular information systems may be intended for use at one or more levels of an organization, as follows (Figure 1.1):
Figure 1.1 Information systems and the levels of an organization.
- The operational level - day-to-day operations and routine decisions. In an airline, for example, an operational decision is whether to cancel a particular flight on a particular day, or what type of aircraft to schedule on a particular flight during the summer flying season. Operational events that that might need to be recorded could include a customer scanning her boarding pass as she boards a flight, or an aircraft arriving at its destination gate.
- The strategic level - the highest-level, "big picture" decisions. In the example of an airline, whether to serve the Asia-US market, or whether to emphasize cost over service quality.
- The tactical level - decisions in between operational and strategic levels; for an airline, such a decision might be whether to increase or decrease service to a particular city.
In reality, the boundaries between these levels are typically somewhat indistinct: the levels form a continuous "spectrum." But labeling different segments of this spectrum as "levels" is useful conceptually.
Organizations are also typically divided into functional areas, meaning that different parts of the organization have different functions (that is, they do different things). These divisions vary by organization, but Figure 1.1 shows a fairly standard division into accounting, finance, operations, marketing, and human resources.
Transaction processing systems (TPSs) gather data about everyday business events in "real time" as they occur. Examples:
- You buy three items at a local store.
- A shipment of coffee beans arrives at a local distribution center.
- A passenger checks in for a flight.
- A package is unloaded from a FedEx or UPS aircraft.
Although only one of the above events is a transaction in the classical economic sense, from an information systems perspective all of these events are examples of transactions that may be immediately tracked by a TPS. Often, technology like barcodes and scanners makes tracking such transactions quicker, cheaper, and more detailed than if their associated data were to be keypunched manually. TPS systems are always operational-level systems, but they may also be used at other levels, or feed information to other systems at higher levels.
Functional area information systems (FAISs), also called departmental information systems (DISs), are designed to be operated within a single traditional functional department of an organization such as sales, human resources, or accounting. In the early days of CBIS, these were often the only kind of systems that were practical, because managing the data from more than one functional area would have required too much storage or computing power for a single system.
When an organization has multiple functional area systems, properly...
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