Making sure that users are able to enter data into the system accurately is of utmost importance. It is by now axiomatic that the quality of data input determines the quality of information output.The systems analyst can support accurate data entry through the achievement of four broad objectives: (1) creating meaningful coding for data, (2) designing efficient data capture approaches, (3) assuring complete and effective data capture, and (4) assuring data quality through validation.
The quality of data is a measurement of how consistently correct the data are within certain preset limits. Effectively coded data facilitate accurate data entry by humans through cutting down on the sheer quantity of data, and thus the time required to enter the information.
When users enter data efficiently, data entry is meeting predetermined performance measures that give the relationship between the time spent on entry and the number of data items entered. Effective coding, effective and efficient data capture and entry, and ensuring data quality through validation procedures are all data entry objectives covered in this chapter.
Ensuring the quality of the data input to the information system is critical to ensuring quality output. The quality of data entered can be improved through effective coding, effective and efficient data capture, and the validation of data.
Data entry by humans can be speeded up through effective use of coding, which puts data into short sequences of digits and/or letters. Both simple sequence codes and alphabetic derivation codes can be used to follow the progress of a given item. Classification codes and block sequence codes are useful for distinguishing classes of items from each other. Cipher codes are also useful because they can conceal information that is sensitive or is restricted to employees.
Codes are also worthwhile for revealing information to users, since they can enable employees to locate items in stock and also make data entry more meaningful. Significant-digit subset codes use subgroups of digits to describe a product. Mnemonic codes also reveal information by serving as human memory aids that can help a data entry operator enter data correctly or help the user. The Unicode character set includes all standard language symbols. You can display Web pages written in other alphabets by downloading an input method editor from Microsoft. Function codes are useful shortcuts for informing computers or people about what functions to perform or what actions to take.
Effective data entry should also consider input devices. A well-designed, effective form that serves as a source document is the first step. Data can be input through many different methods, each with varying speed and reliability. Keyboards have been redesigned for efficiency and improved ergonomics. Optical character recognition (OCR), magnetic ink character recognition (MICR), and mark-sense forms each have special capacities for improving efficiency. Bar codes also speed data entry, improve data accuracy, and increase reliability. RFID allow the automatic collection of data using RFID tags on products, people, or animals. They can improve inventory management and supply chain processes.
Accurate data entry also can be enhanced through the use of input validation. Analysts must work with users to design input validation tests to prevent erroneous data from being processed and stored, which is costly and potentially detrimental.
Input transactions should be checked to ensure the request is acceptable, authorized, and correct. Input data can be validated through software using several types of tests that check for missing data, length of data items, range and reasonableness of data, and invalid values for data. Input data can also be compared with stored data for validation purposes. Once numerical data are input, they can be checked and corrected automatically through the use of check digits and the Luhn formula.
There is a set order for the testing of data to validate each field. There are also pattern validation methods found in the database design or included in programming languages. The patterns are called regular expressions and contain symbols that represent the type of data that must be present in a field.
Ecommerce environments afford the opportunity for increasing accuracy of data. With proper emphasis on user-centered design elements, customers can enter their own data, store data for later use, use the same stored data throughout the order fulfillment process, and receive feedback regarding order confirmations and updates.
Once you have mastered the material in this chapter you will be able to:
- Understand the uses of effective coding to support users in accomplishing their tasks.
- Design effective and efficient data capture approaches for people and systems.
- Recognize how to ensure data quality through validation.
- Articulate accuracy advantages of user input on ecommerce Web sites.