Crud Application

Crud Application

Validation Rules
1. Importance of Data Validation
  1. Ensures Data Accuracy
  2. Ensures Data Integrity
2. CRUD
  1. Create
    1. Ensures data entered adheres to specified standards, formats and constraints
  2. Read
    1. Data being read should already have been validated during create or update
  3. Update
    1. Data consistency
    2. Valid formatting
    3. Valid range and uniqueness
  4. Delete
    1. Cascading effects (e.g., ensuring that deleting a parent records doesn't leave orphaned child records)
3. Types of Validation
  1. Format
    1. Validates data format (e.g., email, phone number)
  2. Range
    1. Validates correct ranges for numeric data such as age of price
    2. Includes the handling of out-of-range values
  3. Presence
    1. Ensured required fields are not left empty
  4. Uniqueness
    1. Ensures unique values for specific fields (e.g. emails, usernames)
    2. Avoids duplication
4. Validation Methods
  1. Client side
  2. Server side
  3. Database constraints
5. Handling errors
  1. Displaying user-friendly error messages
  2. Highlighting specific fields with erroneous data
  3. Provide guidance to the user on how to fix issues
Data Privacy Consideration
1. Importance of Data Privacy
  1. Balancing usability with privacy
2. Data Types
  1. Identifying sensitive and personal data (e.g., first and last names)
  2. Categorising data based on privacy impact
3. Consent
  1. Obtain user consent for data collection and processing
    1. The mechanisms for obstaining said consent
4. Data Minimisation
  1. Collecting only the necessary data for the purposes of the CRUD application
    1. Reduces risk associated with excessive data collection
5. User Access Control
  1. Limit access to only authorised users
  2. Preventing unauthorised access to sensitive information
Data Types
1. Importance of Data Types
  1. Optimise memory storage
  2. Data Integrity and Validation
  3. Error Prevention and Debugging
    1. Code Readability and Maintainability
2. Fundamental data types (e.g., integers, strings)
3. Composite data types (e.g., records, objects)
4. Date and Time Data Types (e.g.,, DD/MM/YYYY)
5. Array and List Data Types (e.g., collections of items)
Required Data
1. Importance of Required Data
  1. Impacts on data completeness and system functionality
2. Mandatory Fields
  1. Identify fields that must be filled during data entry
  2. Preventing incomplete records
3. Application requirements
  1. Understand application processes to determined mandatory data
    1. Allows for the aligning of data requirements with application needs
4. Data Dependency
  1. Recognise data interdependencies that might require for certain fields to be made mandatory
    1. Allows for the ensuring of consistent and meaningful data
5. User Experience
  1. Balancing mandatory fields with user friendliness
  2. Providing clear instructions and error messagse
Limitations of CRUD
1. Limited functionality
2. Scalability
3. Lack of sophisticated UI
4. Basic security

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	Created by Lifan Xu about 2 years ago