MIS 533 Midterm

Give four reasons why a business rules approach is advocated as a new paradigm for specifying information systems requirements.

1. Business rules are a core concept in an enterprise because they are an expression of business policy and guide individual and aggregate behavior. Well-structured business rules can be stated in natural language for end users and in a data model for systems developers. 2. Business rules can be expressed in terms that are familiar to end users. Thus, users can define and then maintain their own rules. 3. Business rules can be expressed in terms that are familiar to end users. Thus, users can define and then maintain their own rules. 4. Enforcement of business rules can be automated through the use of software that can interpret the rules and enforce them using the integrity mechanisms of the database management system

State four criteria for selecting identifiers for entities.

1. Choose an identifier that will not change its value over the life of each instance of the entity type. 2. Choose an identifier such that for each instance of the entity, the attribute is guaranteed to have valid values and not be null (or unknown). 3. Avoid the use of so-called intelligent identifiers (or keys), whose structured indicates classifications, locations, and so on. 4. Consider substituting single-attribute surrogate identifiers for large composite identifiers.

Nine major components in a database system environment:

1. Data modeling and design tools: Data modeling and design tools are automated tools used to design databases and application programs. These tools help with creation of data models and in some cases can also help automatically generate the "code" needed to create the database. We reference the use of automated tools for database design and development throughout the text. 2. Repository: A repository is a centralized knowledge base for all data definitions, data relationships, screen and report formats, and other system components. A repository contains an extended set of metadata important for managing databases as well as other components of an information system. We describe the repository in Chapter 12. 3. DBMS: A DBMS is a software system that is used to create, maintain, and provide controlled access to user databases. We describe the functions of a DBMS in Chapter 12. 4. Database: A database is an organized collection of logically related data, usually designed to meet the information needs of multiple users in an organization. It is important to distinguish between the database and the repository. The repository contains definitions of data, whereas the database contains occurrences of data. We describe the activities of database design in Chapters 4 and 5 and of implementation in Chapters 6 through 9. 5. Application programs: Computer-based application programs are used to create and maintain the database and provide information to users. Key database-related application programming skills are described in Chapters 6 through 9. 6. User interface: The user interface includes languages, menus, and other facilities by which users interact with various system components, such as data modeling and design tools, application programs, the DBMS, and the repository. User interfaces are illustrated throughout this text. 7. Data and database administrators: Data administrators are persons who are responsible for the overall management of data resources in an organization. Database administrators are responsible for physical database design and for managing technical issues in the database environment. We describe these functions in detail in Chapter 12. 8. System developers: System developers are persons such as systems analysts and programmers who design new application programs. 9. End users: End users are persons throughout the organization who add, delete, and modify data in the database and who request or receive information from it. All user interactions with the database must be routed through the DBMS.

State six general guidelines for naming data objects in a data model.

1. Data names should relate to business, not technical characteristics. 2. Data names should be meaningful, almost to the point of being self-documenting. 3. Data names should be unique from the name used for every other distinct data object. 4. Data names should be readable, so the name is structured as the concept would most naturally be said. 5. Data names should be composed of words taken from an approved list. 6. Data names should be repeatable, meaning that different people or the same person at different times should develop exactly or almost the same name.

Project data model:

1. It is a model of the organization that provides valuable information about how the organization functions, as well as important constraints. 2. The project data model focuses on entities, relationships, and business rules. It also includes attribute labels for each piece of data that will be stored in each entity.

List five costs or risks associated with the database approach:

1. New, specialized personnel 2. Installation and management cost and complexity 3. Conversion costs 4. Need for explicit backup and recovery 5. Organizational conflict

Name the five phases of the traditional systems development life cycle and explain the purpose and deliverables of each phase:

1. Planning i. Purpose: To develop a preliminary understanding of a business situation and how information systems might help solve a problem or make an opportunity possible 2. Analysis i. Purpose: To analyze the business situation thoroughly to determine requirements, to structure those requirements, and to select among competing system features 3. Design i. Purpose: To elicit and structure all information requirements; to develop all technology and organizational specifications 4. Implementation i. Purpose: To write programs, build databases, test and install the new system, train users, and finalize documentation 5. Maintenance i. Purpose: To monitor the operation and usefulness of the system, and to repair and enhance the system

Give three reasons why many system designers believe that data modeling is the most important part of the systems development process.

1. The characteristics of the data obtained during the data modeling is crucial in designing the databases, print reports, programs and computer screens. 2. When compared to processes, data is the most complex aspect for many modern information systems. Hence it plays a crucial role in documenting system requirements. 3. The information used in the data modeling can be used in identifying primary keys, foreign keys, relational tables, procedures and triggers. 4. The structured information about data is extremely important for generating the programs automatically.

What is the degree of a relationship? List the three types of relationship degrees described in the chapter and give an example of each.

1. Unary Relationship is a relationship between the instances of a single entity type. They are also called Recursive Relationships. 2. Binary Relationship is a relationship between the instances of two entity types and is the most common type of relationship encountered in data modeling. 3. Ternary Relationship is a simultaneous relationship among the instances of three entity types.

State three conditions that suggest the designer should model a relationship as an associative entity type.

1. many-many relationship 2. has independent meaning for the end uses 3. the identifier has one or more attributes 4. take part in one or more relationship of the independent entities that are related in the associated relationship

entity type:

A collection of entities that share common properties or characteristics.

composite attribute:

A composite attribute is an attribute, such as Address, that has meaningful component parts, which are more detailed attributes.

Relational Database:

A database that represents data as a collection of tables in which all data relationships are represented by common values in related tables

Conceptual schema:

A detailed, technology independent specification of the overall structure of organizational data.

entity:

A person, a place, an object, an event, or a concept in the user environment about which the organization wishes to maintain data.

attribute:

A property or characteristic of an entity or relationship type that is of interest to the organization.

unary relationship

A relationship between instances of a single entity type.

binary relationship:

A relationship between the instances of two entity types.

required attribute; optional attribute

A required attribute is an attribute that must have a value in it, while an optional attribute may not have a value in it and can be left blank. The reasoning for making an attribute required is to ensure that data are collected for that particular characteristic.

ternary relationship:

A simultaneous relationship among the instances of three entity types.

entity instance:

A single occurrence of an entity type.

DBMS

A software system that is used to create, maintain, and provide controlled access to user databases.

stored attribute; derived attribute:

A stored attribute is an attribute that cannot be derived from other attributes while a derived attribute is an attribute that can be obtained using another stored attribute.

Give an example, other than those described in this chapter, of a weak entity type. Why is it necessary to indicate an identifying relationship?

A weak entity type would be a ROOM because it cannot exist without constructing a BUILDING. It is necessary to indicate an identifying relationship in order to understand the relationship between the two entities.

identifier:

An attribute (or combination of attributes) whose value distinguishes instances of an entity type.

multivalued attribute:

An attribute that may take on more than one value for a given entity (or relationship) instance.

derived attribute:

An attribute whose values can be calculated from related attribute values.

Enterprise Applications:

An enterprise application/database is one whose scope is the entire organization or enterprise (or, at least, many different departments). Such databases are intended to support organization-wide operations and decision making. Note that an organization may have several enterprise databases, so such a database is not inclusive of all organizational data

strong entity:

An entity that exists independently of other entity types.

associative entity:

An entity type that associates the instances of one or more entity types and contains attributes that are peculiar to the relationship between those entity instances.

weak entity:

An entity type whose existence depends on some other entity type.

Prototyping:

An iterative process of systems development in which requirements are converted to a working system that is continually revised through close work between analysts and users.

Database:

An organized collection of logically related data

composite attribute; multivalued attribute:

Composite attributes can be divided into subparts. For example, an attribute name could be structured as a composite attribute consisting of first-name, middle-initial, and last-name. There may be instances where an attribute has a set of values for a specific entity. Consider an employee entity set with the attribute phone-number. An employee may have zero, one, or several phone numbers, and different employees may have different numbers of phones

Metadata:

Data that describe the properties or characteristics of end-user data and the context of those data.

Information:

Data that have been processed in such a way as to increase the knowledge of the person who uses the data.

ternary relationship; three binary relationships:

Don't be confused: A ternary relationship is not the same as three binary relationships. For example, Unit Cost is an attribute of the Supplies relationship in Figure 2-12c. Unit Cost cannot be properly associated with any one of the three possible binary relationships among the three entity types, such as that between PART and WAREHOUSE. Thus, for example, if we were told that vendor X can ship part C for a unit cost of $8, those data would be incomplete because they would not indicate to which warehouse the parts would be shipped.

Structured data:

For example, in a salesperson's database, the data would include facts such as customer name, address, and telephone number. This type of data is called structured data. The most important structured data types are numeric, character, and dates. Structured data are stored in tabular form (in tables, relations, arrays, spreadsheets, etc.) and are most commonly found in traditional databases and data warehouses.

Unstructured data:

For example, the salesperson's database might include a photo image of the customer contact. It might also include a sound recording or video clip about the most recent product. This type of data is referred to as unstructured data, or as multimedia data.

Personal Databases:

Personal databases are designed to support one user. Personal databases have long resided on personal computers (PCs), including laptops, and now increasingly reside on smartphones, tablets, phablets, etc. The purpose of these databases is to provide the user with the ability to manage (store, update, delete, and retrieve) small amounts of data in an efficient manner

In addition to explaining what action is being taken, what else should a relationship definition explain?

Relationship is used to connect entity types in a meaningful way. It means that those questions which are not answered by the entity type can be answered by the relationship type.

How are relationships between tables expressed in a relational database?

Relationships between tables are expressed by identical data values stored in the associated columns of related tables in a relational database.

simple attribute; composite attribute:

Simple attribute − Simple attributes are atomic values, which cannot be divided further. For example, a student's phone number is an atomic value of 10 digits. Composite attribute − Composite attributes are made of more than one simple attribute. For example, a student's complete name may have first_name and last_name.

Physical schema:

Specifications for how data from a logical schema are stored in a computer's secondary memory by a database management system.

strong entity type; weak entity type:

Strong entity always has primary key. While weak entity has partial discriminator key. 2. Strong entity is not dependent of any other entity. Weak entity is dependent on strong entity. 3. Strong entity is represented by single rectangle. Weak entity is represented by double rectangle. 4. Two strong entity's relationship is represented by single diamond. While the relation between one strong and one weak entity is represented by double diamond. 5. Strong entity has either total participation or not. While weak entity always has total participation

identifying owner:

The entity type on which the weak entity type depends.

Enterprise data model:

The first step in database development, in which the scope and general contents of organizational databases are specified.

identifying relationship:

The relationship between a weak entity type and its owner.

Logical schema:

The representation of a database for a particular data management technology

What does the term data independence mean, and why is it an important goal?

The separation of data descriptions (metadata) from the application programs that use the data is called data independence. With the database approach, data descriptions are stored in a central location called the repository. This property of database systems allows an organization's data to change and evolve (within limits) without changing the application programs that process the data.

Data Independence:

The separation of data descriptions from the application programs that use the data.

External Schema:

This is the view (or views) of managers and other employees who are the database users.

Describe the Multitier Client/Server database architecture:

To overcome these limitations, most modern applications that need to support a large number of users are built using the concept of multitiered architecture. In most organizations, these applications are intended to support a department (such as marketing or accounting) or a division (such as a line of business), which is generally larger than a workgroup (typically between 25 and 100 persons).

Rapid Application Development:

Which follow an iterative process of rapidly repeating analysis, design, and implementation steps until they converge on the system the user wants. These RAD methods work best when most of the necessary database structures already exist, and hence for systems that primarily retrieve data, rather than for those that populate and revise databases.

business rule:

a statement that defines or constrains some aspect of the business. It is intended to assert business structure or to control or influence the behavior of the business ...rules prevent, cause, or suggest things to happen

Data

a stored representation of objects and events that have meaning and importance in the user's environment

Internal schema:

an internal schema today really consists of two separate schemas: a logical schema and a physical schema. The logical schema is the representation of data for a type of data management technology (e.g., relational). The physical schema describes how data are to be represented and stored in secondary storage using a particular DBMS (e.g., Oracle)

entity type; relationship type:

entity types are like nouns. And object that we want to store data about (Customer and Invoice). Relationship types are how those nouns relate to each other... like verbs (received and sent)

entity-relationship model:

is a detailed, logical representation of the data for an organization or for a business area. The E-R model is expressed in terms of entities in the business environment, the relationships (or associations) among those entities, and the attributes (or properties) of both the entities and their relationships

Entity:

is like a noun in that it describes a person, a place, an object, an event, or a concept in the business environment for which information must be recorded and retained

disadvantages of file management approach:

· Program-Data Dependence · Duplication of Data · Limited Data Sharing · Lengthy Development Times · Excessive Program Maintenance