Module1IntroductiontoDataEntryinSystemDevelopment.pdf

INTRODUCTION TO DATA ENTRY IN SYSTEM DEVELOPMENT DESIGNING ACCURATE DATA ENTRY PROCEDURES, EFFECTIVE CODING DATA CAPTURE ENSURING DATA QUALITY PREPARED BY: LAURICE M. MARIQUINA IT 301 / CS 301: SOFTWARE ENGINEERING 2 ...

INTRODUCTION TO DATA ENTRY IN SYSTEM DEVELOPMENT DESIGNING ACCURATE DATA ENTRY PROCEDURES, EFFECTIVE CODING DATA CAPTURE ENSURING DATA QUALITY PREPARED BY: LAURICE M. MARIQUINA IT 301 / CS 301: SOFTWARE ENGINEERING 2  01 04 Understand the importance of Discuss methods for effective accurate data entry in system and efficient data capture. LESSON development. OBJECTIVES: 02 05 Identify best practices for Implement input validation designing data entry techniques to ensure data procedures. quality. 03 Explain the principles of effective coding in software engineering. Data Entry: The process of inputting data into a system. Accurate data entry is critical because errors at this stage can propagate through the system, leading to incorrect outputs and decisions. Importance: Data integrity: Ensures that the data within a system remains accurate, consistent, and reliable. System reliability: Accurate data entry supports the overall reliability of the system. User trust: Users are more likely to trust and use systems that consistently provide accurate information. DESIGNING ACCURATE DATA ENTRY PROCEDURES  BEST PRACTICES: 1.SIMPLIFY USER INTERFACES: 3. USE DROP-DOWN LISTS AND RADIO BUTTONS: Design forms with clear, concise labels and logical grouping of related fields. Where applicable, use drop-down lists or Minimize the number of fields to reduce the radio buttons instead of free text to limit the potential for errors. scope of input and reduce errors. 4. INPUT MASKS: 2. PROVIDE DEFAULT VALUES AND Implement input masks for fields like phone AUTO-COMPLETION: numbers or dates to enforce consistent formatting and reduce input errors. Use default values for common fields to speed up data entry. 5. CLEAR INSTRUCTIONS AND FEEDBACK: Implement auto-completion for repetitive Provide users with clear instructions on how tasks to reduce user effort and error rates. to enter data. Implement real-time feedback to alert users to errors as they occur. EFFECTIVE CODING PRACTICES CODING STANDARDS AND CONVENTIONS: Consistency: Adhere to consistent naming conventions and code formatting to make code more readable and maintainable. Commenting: Write clear comments to explain complex logic or decisions in the code, helping future developers understand and maintain the codebase. Modularity: Break down code into reusable modules or functions to improve organization and reduce redundancy. Error Handling: Implement robust error handling to catch and respond to potential issues gracefully, ensuring system stability. EFFICIENCY IN CODING: Optimize Algorithms: Choose the most efficient algorithms to perform tasks, reducing computational load and improving system performance. Avoid Redundancies: Eliminate redundant code and operations that do not contribute to the functionality. Code Reviews: Regularly review code with peers to identify potential issues and areas for improvement. EFFECTIVE AND EFFICIENT DATA CAPTURE METHODS OF DATA CAPTURE: : Manual Data Capture: Involves users manually entering data into the system. Best suited for small volumes of data or when automated methods are not feasible. Automated Data Capture: Utilizes technologies like barcode scanners, RFID, and OCR to capture data automatically. Reduces human error and speeds up the data entry process. METHODS OF DATA CAPTURE: Efficiency Considerations: Batch Processing: Where possible, process data in batches to reduce system load and improve efficiency. Real-time Data Capture: Implement real-time data capture where necessary, ensuring that the system is always up-to-date. ENSURING DATA QUALITY THROUGH INPUT VALIDATION WHAT IS INPUT VALIDATION? The process of verifying that the data entered into a system meets predefined criteria and is suitable for processing. INPUT VALIDATION TECHNIQUES: Range Checks: Ensure that numerical inputs fall within a specified range. Example: A field for age should only accept values between 0 and 120. Format Checks: Verify that data conforms to a specific format. Example: An email address must contain a "@" symbol and a valid domain. Mandatory Fields: Ensure that all required fields are filled before data submission. Example: Prevent form submission if a required field is empty. Consistency Checks: Compare input data with other related data to ensure consistency. Example: If a start date is entered, it must be before the end date. Cross-Validation: Validate data across different fields to ensure logical consistency. Example: Ensure that the total sum of all line items equals the invoice total. BEST PRACTICES: Client-Side Validation: Implement basic validation on the client side to provide immediate feedback to users. Server-Side Validation: Always validate data on the server side to prevent malicious input or bypassing of client-side checks. User-Friendly Error Messages: Provide clear and helpful error messages when validation fails, guiding users to correct their input. REFERENCES: OWASP Data Validation: Software Engineering Coding Standards Automated Data Capture Techniques: THANK YOU