Systems Analysis & Design II, Topic 10

Systems Analysis & Design II, Topic 10: Designing Accurate Data Entry Procedures

• This topic focuses on designing accurate data entry procedures for systems.
• The learning objectives include understanding effective coding and designing efficient data capture methods.
• Effective coding reduces data entry time, decreases errors, and optimizes memory usage during data transformation.
• Coding ensures consistent data structure, allows sorting, and ensures data uniqueness.
• Coding helps organize data and improve efficiency.
• Common coding methods include simple sequence and alphabetic derivation codes.
• Simple sequence codes involve assigning a number to a data item without reference to the data itself, like order numbers.
• Alphabetic codes derive data item codes from the characteristics of an item, like a customer ID.
• Stability in codes requires maintaining consistent coding for an item throughout, avoiding conflicts.
• Concise codes mean shorter codes, easier memorization, and fewer errors in data entry.
• Unique codes prevent repeats and maintain sorting accuracy.
• Sortable codes allow easy organization and retrieval of data.
• Distinguishing codes should be non-confusing to avoid errors; avoid look-alike characters.
• Uniform codes ensure consistency, making them easy to use and understand across a system.
• Modifiable codes allow the coding system to adapt to changes over time as the system evolves.
• Meaningful codes contain important information related to the data they describe; codes must be meaningful to end users.
• Effective data input methods include deciding what data to capture, letting the computer handle the rest, avoiding bottlenecks, using good forms and selecting a reliable data entry method.
• Data capture methods include input via keyboards, optical character recognition (OCR), magnetic ink character recognition (MICR), mark-sense forms, bar codes, and RFID.
• Keyboards accommodate special function keys, web navigation, programmed macros to reduce keystrokes, and include ergonomic options like infrared or Bluetooth keyboards.
• OCR increases data entry speed, eliminating many steps of other input methods and decentralizing responsibilities.
• MICR accuracy and speed and is not susceptible to stray marks, providing security against bad checks.
• Mark-sense form methods are quick to use with little input training; however, stray marks can result in errors and the choices available are limited.
• Bar codes improve accuracy, reduce labor costs during entry, and automatically capture data with high reliability.
• RFID automatically collects data via embedded chips and antennas, though privacy is a concern.
• Data validation catches errors during data input, helps validate transactions, and helps validate entered data.
• Validation techniques include testing for missing data, correct field lengths, class/composition compliance, range/reasonableness conformance, invalid value tests, cross-reference checks, comparison with stored data, and using self-validating codes like check digits.
• Validation is crucial for ensuring data integrity in various applications.

Subtopics (Output)

• Effective Coding: Covers general coding guidelines.
• Effective and Efficient Data Capture: Includes choosing a data entry method.