Crud Application

Crud Application

1. 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

2. 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

3. 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)

4. 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

5. Limitations of CRUD

   • Limited functionality
   • Scalability
   • Lack of sophisticated UI
   • Basic security