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