Chapter 9 Data Dictionaries system analysis and design.pptx

SAD lecture notes

1. Course: CSC1108 - System Analysis & Design Semester: January 2024 Lecturer: Ms Jayashiry Morgan

2. Recap: How does interviewing works for analysis phase? How to choose the right interview questions? Analyze DFD Create DFD

3. Chapter 9: Data Dictionaries

4. Learning Outcome By the end of this session, students should be able to identify and calculate: What is data dictionary? What are the contents of data dictionary? Explain. How the data dictionary can be used?

5. Data Dictionary A data dictionary contains metadata i.e. data about the database. It contains information such as what is in the database, who is allowed to access it, where is the database physically stored etc. It plays an important role in building a database.

6. Data Dictionary

7. Data Dictionary The data dictionary in general contains information about the following: Names of all tables in the database Names of each field in the tables of the database Constraints defined on tables Physical information about tables like their storage location, storage method, etc.

8. Data Dictionary The users of the database normally don’t interact with the data dictionary, it is only handled by the database administrator. A data dictionary is also called a metadata repository. There are two types of data dictionary: Active Passive

9. Types of Data Dictionary Active It may happen that the structure of the database has to be changed, like adding new attributes or removing older ones. If those changes are updated automatically in the data dictionary by the DBMS, then the data dictionary is an active one. It is also known as integrated data dictionary.

10. Types of Data Dictionary Passive When the DBMS maintains the data dictionary separately and it must be updated manually, then the data dictionary is a passive one. It is also known as non-integrated data dictionary. In this case, there is a chance of mismatch with the database objects and the data dictionary.

11. Key Components of a Data Dictionary Data Element Name: This is the unique identifier for each data element within the system. It should be descriptive and meaningful to facilitate understanding.

12. Key Components of a Data Dictionary 2. Data Type: Specifies the kind of data that a particular data element can hold, such as integer, string, date, etc. Defining data types ensures consistency and accuracy in data storage and manipulation.

13. Key Components of a Data Dictionary 3. Data Length: Indicates the maximum number of characters or digits that a data element can accommodate. Helps in determining storage requirements and ensuring data integrity.

14. Key Components of a Data Dictionary 4. Description: Provides a detailed explanation or definition of the data element. Clarifies the purpose, meaning, and usage of the data for users and developers.

15. Key Components of a Data Dictionary 5. Allowable Values: Provides a detailed explanation or definition of the data element. Clarifies the purpose, meaning, and usage of the data for users and developers.

16. Key Components of a Data Dictionary 6. Default Value: Specifies the value that is automatically assigned to a data element if no other value is provided. Useful for ensuring consistency and completeness in data entry.

17. Key Components of a Data Dictionary Validation Rules: Defines the criteria or conditions that must be met for data to be considered valid. Includes formats, ranges, and constraints applied to data elements.

18. Key Components of a Data Dictionary 8. Relationships: Describes the connections or associations between different data elements. Helps in understanding how data elements relate to each other within the system.

19. Key Components of a Data Dictionary Usage Notes: Provides additional information or instructions on how to use the data element. Offers guidance to users and developers for proper handling and interpretation of data.

20. Benefits of Using Data Dictionary Improved Data Understanding: Data dictionaries provide clear and detailed documentation of data elements, enhancing understanding among stakeholders. 2. Enhanced Data Consistency: By defining data types, lengths, and validation rules, data dictionaries ensure consistency and accuracy in data storage and usage.

21. Benefits of Using Data Dictionary Facilitated System Development: Developers can reference data dictionaries to understand data requirements and design database schemas more efficiently. 4. Simplified Data Maintenance: Changes to data structures or definitions can be easily managed and updated in the data dictionary, ensuring consistency across the system.

22. Benefits of Using Data Dictionary 5. Support for Data Governance: Data dictionaries serve as valuable assets for data governance initiatives by providing transparency and accountability in data management. Improved Data Quality By specifying allowable values and validation rules, data dictionaries help maintain data quality and integrity throughout the system lifecycle.

23. Data Dictionary Contents Data flow Data structures Elements Data stored

24. Data Flow Each data flow should be defined with descriptive information and its composite structure or elements Include the following information: ID Label A general description of the data flow The source of the data structure or elements The name of the data structure or elements The volume per unit time An area for further comments and notations about the data flow

25. Data Flow Example

26. Data Structures Data structures are a group of smaller structures and elements An algebraic notation is used to represent the data structure

27. Elements Data elements should be defined with descriptive information, length and type of data information, validation criteria, and default values. Each element should be defined once in the data dictionary. Attributes of each element are: Element ID The name of the element, descriptive and unique Aliases, which are synonyms or other names for the element A short description of the element Whether the element is base or derived The length of an element

28. Elements What should the element length be? Some elements have standard lengths, such as a state abbreviation, zip code, or telephone number For other elements, the length may vary, and the analyst and user community must decide the final length

29. Data Element Example

30. Data Stores Data stores contain a minimal of all base elements as well as many derived elements. Data stores are created for each different data entity; that is, each different person, place, or thing being stored.

31. Data Store Example

32. Conclusion Data dictionaries play a crucial role in effective data management and system development. By providing comprehensive documentation of data elements and their attributes, data dictionaries facilitate understanding, consistency, and quality in data usage. Incorporating data dictionaries into the development process can lead to more efficient and reliable information systems.

33. Class Activity #1 Divide into 2 groups. Create a data dictionary for the following dataset, specifying the data type and data length where relevant. Upload your work in Teams > Class Materials > Students Work (One person from each group upload) DATA NAME SAMPLE DATA employeeID 123456 employeeName John Smith department Marketing jobTitle Senior Analyst hireDate 2020-05-15 salary 50000 phoneNumber 123-456-7890 emailAddress [email protected] address 123 Main Street, Cityville , State, ZIP isActive true

34. ANSWER DATA NAME SAMPLE DATA DATA TYPE DATA LENGTH employeeID 123456 Integer 6 employeeName John Smith String 20 department Marketing String 15 jobTitle Senior Analyst String 20 hireDate 2020-05-15 Date 10 salary 50000 Integer 5 phoneNumber 123-456-7890 String 12 emailAddress [email protected] String 30 address 123 Main Street, Cityville, State, ZIP String 50 isActive true Boolean -

35. Data Types & Example (Activity #2) Each student to find data type (that was not mentioned in the lecture notes/activity) Shouldn't be same with others. One person = one data type with example

36. Class Activity #3 - Data Dictionary Scavenger Hunt Remain in the same groups. Each group to create a data dictionary for the following dataset, leaving blank spaces for the data type and data length (like the table in Class Activity #1) – 10 minutes : Group 1: Student information system Group 2: P roduct inventory management system Each group to draw the table prepared in the whiteboard (5 minutes). Must have total 10 rows of data . After hearing buzzer sound, switch places and start filling up the blank spaces (data types and data length) in the data dictionary prepared by the opposite team. Winner is the fastest and the most correct answers team.