data preparation is pre-processing of "raw" data before a batch data entry input. Data that is to be used to update a master file needed to be carefully prepared. There are processes a data will pass through before it can be useful and suitable for use on a master file. They include. coding, data entry, data verification and data validation.
Data Preparation (coding): This is a process of updating or getting the data ready for entry into the computer. Coding of data is the method by which raw facts received for updating are converted into means which will be easy for data entry operators to capture with speed. There are some laws guiding data preparation/coding. These laws are as follows:
Uniformity in the way data is entered.
For example, capital and small letters of the alphabets should be used carefully.
There must be proper punctuation.
Numbers should be entered carefully.
These laws are necessitated by the fact that anything entered into computer incorrectly will result in incorrect result as the computer will not make any corrections.
Data Entry: This is the process of transferring the prepared data into the computer. This may involve adding new data, editing old data and deleting unwanted data. The method used in data entry depends to a large extent on the type of data one intends to enter.
Data Verification: This is a process of ensuring that a record is correctly captured. The beauty of it is that the captured item will be recaptured by another operator to compare the already captured one.
Data Validation: Data validation is usually done by the computer after verification, the entire captured items will be taken to the master file to test their validity. By so doing the computer will check whether any of the data captured exist, if for instance any one is found incorrect or does not exit, the computer will flag such data for correction.
Data Editing and Update: It is however, possible that in spite of preparation before data , all computer operators are prone to some errors, and that is why data validation and verification is important. The process of correcting these errors is called data editing. Once editing is effected the corrected version is used to replace the old record and again any records that are not required can be removed at this stage. The process of editing records to ensure that they are up to data is called updating.
DATA MODEL
A data model may be defined as a way of finding tool for both business and IT professionals, which uses a set of symbols and text to precisely explain a subset of real information to improve communication within the organization and thereby lead to a more flexible and stable application.
A data model explicitly determines the structure of data or structured data. Typical applications of data models include database models, design of information systems, and enabling exchange of data. Usually data models are specified in data modeling language.
Communication and precision are the two key benefits that make a data model important applications that used and exchange data. A data model is the medium which project team members from different background and with different levels of experience. A data model can be sometimes referred to as a data structure, especially in the context of programming language.
DATA DIGISTALISATION
This is information represented by a code consisting of a sequence of discrete elements.
Data Origination: The translation of information from its original form into a machine readable form or directly into electrical signals.
COMPUTER DATA CONVERSION
Computer data conversion may be described as the conversion of computer data from one format to another. For example to convert megabytes to Kilobytes or vice versa.
Address: Is an identification, as represented by a name, label, or number, for a register, location of a station in a communication network. Loosely, any part of an instruction that specifies the location of an operand for the instruction.
Register: This is a device capable of storing a specified amount of data, such as one word.
Home
›
computer data conversion
›
data digistalisation
›
data editing
›
data mode
›
data preparation coding
›
data validation
›
data verification