Tài liệu Module 4: Deriving a Logical Data Design docx

Module 4: Deriving a Logical Data Design THIS PAGE LEFT INTENTIONALLY BLANK Module 1: Course Overview Module 4: Deriving a Logical Data Design Module 5: Normalizing the Logical Data Design Module 6: Deriving a Physical Data Design Module 7: Implementing Data Integrity Module 2: Solution Design Processes Module 3: Using a Conceptual Design for Data Requirements Module 8: Designing Data Services Module 9: Data Storage Considerations Designing Data Services and Data Models Logical Data Design Entities and Attributes Activity 4.1: Deriving Entities and Attributes from Data Requirements Data Relationships Entity/Relationship Modeling Activity 4.2: Creating a Logical Data Model Module 4: Deriving a Logical Data Design Module 4: Deriving a Logical Data Design 67 ! !! ! Overview " Logical Data Design " Entities and Attributes " Data Relationships " Entity/Relationship Modeling " Review In this module In this module At the end of this module, you will be able to: " Analyze data requirements to determine data entities and attributes. " Analyze data entities and attributes to determine their relationships. " Determine the cardinality and existence characteristics of a relationship. " Create an entity/relationship diagram. Slide Objective To provide an overview of the module topics and objectives. Lead-in In this module, you will learn about logical data design and entity/relationship modeling. 68 Module 4: Deriving a Logical Data Design ! !! ! Logical Data Design " The Need for a Logical Data Design " Deriving Logical Data Services In this section In this section In this section, you will learn about logical data design. During this stage of the design process, you will develop a data structure and formalize the solution’s conceptual design. Slide Objective To introduce the concept of logical data design. Lead-in This section discusses the logical data design of a solution. Module 4: Deriving a Logical Data Design 69 The Need for a Logical Data Design " A logical data design: $ Translates conceptual data needs into real data requirements $ Helps organize thinking about the data $ Focuses on the semantic details of data relationships $ Provides a mechanism for communication The logical data design is the middle stage of the natural progression from conceptual design to physical design. The process of deriving a logical data design from the conceptual data design accomplishes the following: " Translates conceptual data needs into real data requirements. You must turn the conceptual data needs identified during conceptual design into actual entities and relationships that will define how the data interacts. " Helps organize your thinking about the data. You must ensure that the data elements identified in the conceptual design stage accurately depict the desired data for the business solution. " Focuses on the semantic details of the data relationships. You are forced to delve deeper into the solution’s data requirements and look at how data interacts within both the existing system and the proposed solution. " Provides a mechanism for communication. The logical design helps to document the data design for all interested parties to read and understand. Slide Objective To discuss the reasons why a logical data design is necessary. 70 Module 4: Deriving a Logical Data Design Deriving Logical Data Services " Organize data requirements into entities " Identify data services " Identify logical groups of services " Identify the relationship between groups and entities " Refine the design Some of the questions that must be addressed during logical data design concern the data services, which determine how the data will be managed and manipulated. Development of a logical design provides a road map of these services. Organize data requirements into entities After the data requirements for a set of use cases have been collected, you need to organize these data requirements into similar groups of information. The groupings of requirements are referred to as entities. The entities allow you to track all of the required data on a given subject. Identify data services It is important to identify any services that will act upon data. For example, consider the timesheet from the Ferguson and Bardell, Inc. case study. Many steps must be taken to complete the timesheet during its life span. Many employees will edit the timesheet or read its information. An automated process may extract timesheet information into another database for reporting purposes. After determining how a particular entity will be used, you determine whether a service should exist that will act as the interface to that entity. Identify logical groups of services " While developing the data services, you might find it beneficial to group services that act upon common data or upon common processes. These groups of services can help bring consistency to the solution, whether they concern a process that manipulates an employee object or a set of objects that deal with bank accounts. Slide Objective To introduce the logical data services. Lead-in When developing a solution, you must address questions regarding the data services. Module 4: Deriving a Logical Data Design 71 For example, consider the consultant, consultant manager, and administrative assistant from the Ferguson and Bardell, Inc. case study. All of them have a need to interact, to some degree, with time and billing information that is stored in the system. One data service might handle the submittal of timesheets from the consultants. A second data service might handle the processing of timesheet data into billable data for the administrative assistants. The fact that all users of the Ferguson and Bardell, Inc. system need to work with timesheet data does not necessarily mean that one all-encompassing data service should handle everything that needs to be done to the timesheet as a single category of data. " After the logical data services are grouped by functionality, you can design data services that handle the logical functionality needed by the solution. Identify the relationship between groups and entities " The data that the services act upon typically does not exist in a vacuum and most real-life situations require that some type of relationship exist between data. Relationships between the services and data should be clearly defined. Identifying the relationships provides greater logical design definition and enhances the functionality of the logical design. " At the logical level, it is important to know what relationships exist between data. Later, these relationships will become part of the logical data model, which is a representation of the data; the users will work with the logical data model on a daily basis. " By identifying all the possible relationships, the development team can better understand the complete picture. Refine the design " After organizing and analyzing entities, you will have to revisit the initial design and make refinements where necessary. This reiteration through the design is a necessary process that will yield a more thorough and complete design. 72 Module 4: Deriving a Logical Data Design ! !! ! Entities and Attributes " Overview of Entities and Attributes " Deriving Entities " Deriving Attributes " Activity 4.1: Deriving Entities and Attributes from Data Requirements In this section In this section In this section, you will learn about logical entities and their attributes as represented in a logical model. Slide Objective To introduce entities and attributes. Lead-in The data services are represented in the logical design by entities and attributes. Module 4: Deriving a Logical Data Design 73 Overview of Entities and Attributes " Entities and their corresponding attributes are the building blocks of relational design " An entity is anything about which data will be collected and stored $ An entity is a noun $ Instances of entities are stored in the rows of a table " An attribute is a characteristic of an instance of an entity $ Attributes are the adjectives $ Attributes are stored in the columns of a table When you move into the logical stage of data design, one of your first tasks is to formulate entities from data requirements and other related information. An entity can be thought of as any person, place, thing, or concept that defines data or about which data will be collected and stored. An attribute is a characteristic that further defines and describes the properties of an instance of an entity. An entity can have multiple attributes. Think of entities as nouns and attributes as adjectives. Entities and attributes identified during logical design will be used later to help model the physical design. Slide Objective To introduce the fundamental concepts of entities and attributes. Lead-in Entities and attributes form the basis for logical design. 74 Module 4: Deriving a Logical Data Design Deriving Entities " Entities represent real-world objects about which information will be stored " When deriving entities, look for nouns or noun phrases during analysis " Rows in database tables " Common examples $ People $ Books When deriving entities, keep in mind that entities are: " Objects about which information will be stored. The entities are the objects about which you wish to retain information. Some examples of entities are Employees, Clients, and Timesheets. " The starting point for the logical data design. The identification of these entities is the first step in the design of a database. " The equivalent of rows in database tables. An instance of an entity will correspond to a row of a table. During requirements analysis, the following techniques will help you derive entities: " Find use cases from gathered information. " Look, or listen, for nouns or noun phrases within the use cases. Nouns describe people, places, things, or concepts. Consider the following example: “Consultants enter their time into a timesheet on a weekly basis. The timesheet is then forwarded to the administrative assistant, who keys the time into the invoicing program. The administrative assistant then sends invoices to the customers based on the time reported.” The italicized words are possible candidates for entities. After you have identified the entities, it is sometimes useful to write a short, one-sentence entity definition that will help determine relationships at a later time. Slide Objective To introduce methods for extracting entities from data requirements. Lead-in When deriving the entities of a solution, keep the following factors in mind. Delivery Tip Point out that entities can represent anything, from people to books to hats. [...]... together and provide advanced capabilities within the logical data design You will also learn how relationships can be further defined by looking at their cardinality and existence 78 Module 4: Deriving a Logical Data Design Overview of Data Relationships Slide Objective To introduce data relationships Lead-in Data relationships are an integral component of a logical data model " Represent associations... Module 8: Designing Data Services Module 7: Implementing Data Integrity Module 2: Solution Design Processes Designing Data Services and Data Models Module 6: Deriving a Physical Data Design Module 4: Deriving a Logical Data Design Module 5: Normalizing the Logical Data Design In the next module, you will learn about: " Defining keys " Normalization strategies: • First form • Second form • Third form Module. .. this activity, you will analyze a single aspect of a logical data design At the end of each exercise, the class will discuss the design that you derived After completing this activity, you will be able to: " Identify and derive data entities from use cases " Identify attributes of the derived data entities Module 4: Deriving a Logical Data Design 77 ! Data Relationships Slide Objective To introduce data. .. relationship, which has more than one instance Existence is denoted by the line style A solid line indicates that a relationship is mandatory, and a broken, or dashed, line indicates that a relationship is optional 86 Module 4: Deriving a Logical Data Design Creating the Logical Data Model Slide Objective To introduce the logical model after it has been assembled by using a defined syntax Lead-in After... logical data model Existence is denoted as a solid or dashed line Lead-in Before an entity relationship diagram can be drawn, a specific syntax has to be defined The logical data model is represented by a drawing known as an entity/relationship (ER) diagram This diagram uses a general syntax to denote the entities, attributes, relationships, cardinality, and existence that constitute the logical data model... Bardell, Inc case study In each of the two exercises in this activity, you analyze a single aspect of a logical data design At the end of each exercise, the class will discuss the design that you derived At the end of this activity, you will be able to: " Identify relationships between entities " Create a logical data model Module 4: Deriving a Logical Data Design ! Review Slide Objective To explain the... Have a logical system design " Use entity/relationship diagrams " Choose the appropriate tools The following are a few guidelines to keep in mind when designing data services and objects Having a logical design makes it easier to develop the physical design because the logical design provides an overall picture and can aid in using resources Entity/relationship diagrams are useful both in the logical. .. a Logical Data Design ! Entity/Relationship Modeling Slide Objective To introduce the topics in this section Lead In This section looks at how the relationships between entities are represented in a logical data model " Syntax " Creating the Logical Data Model " Activity 4.2: Creating a Logical Data Model In this section In this section In this section, you will learn how to create a logical data. .. entities and attributes? Attributes describe entities 3 Why is an ER diagram useful? It provides a layout of the database and can be used for changes and training 91 92 Module 4: Deriving a Logical Data Design Looking Forward Slide Objective To explain where you will go from here Module 9: Data Storage Considerations Lead-in The next module discusses the following topics Module 1: Course Overview Module. .. logical design of the solution and as documentation for future changes or training Many tools exist that can aid in all areas of developing a solution, from the conceptual design, to the definition of database tables, to the actual written code Module 4: Deriving a Logical Data Design Review Questions Slide Objective To reinforce the module s objectives by reviewing key points " Analyze data requirements . introduce data relationships. Lead-in Data relationships are an integral component of a logical data model. Module 4: Deriving a Logical Data Design. reasons why a logical data design is necessary. 70 Module 4: Deriving a Logical Data Design Deriving Logical Data Services " Organize data