Data Processing and Data Storage Hierarchy

 Data Processing - 

Data is collection of facts - unorganized, but able to organized into useful information. A collection of sells orders, employee time sheets, and class attendance cards are a few examples. We can manipulate data to produce output, such as bills, employee salary slip, and student attendance reports. This output, called information, is organized facts that help people to make decisions. Hence, information is data arranged in an order and from that is useful to people who receive it.

Processing, in general terms, is a series of actions or operations that coverts some input into useful output. In data processing, input is data, and useful output is information. Hence, Data processing is a series of actions or operations that converts data into information. 

It consists of three sub activities - 

Capturing input data.

Manipulating input data.

Producing output information.

Data processing system consists of  resources such as people, procedures, and devices, which is used to input data for producing desirable output. Hence, data is a raw material of information, and just as a manufacturing process transforms raw material into finished products, data processing transforms raw data into information. 

Data storage hierarchy

Data processing deals with operation on data. For convenience, system designers define these operations on different levels of aggregated data. These levels from the data storage hierarchy of data processing.

In following figure shows the six levels, which standard data organization mechanisms use in this hierarchy. They are described below.

1. Bit: Smallest item of a data is a single binary digit (a bit), either a 0 or 1.

2. Character: A character is a combination of multiple related bits. For example, M, 8, and $ are characters. A bit is a basic unit of primary and secondary storage, and a character is basic unit of human perception.

3. Field: A field is a combination of multiple related characters. For example, if  we are processing employees' data of a company, we may have one field each for employee code, employee name, worked hours, hourly per rate, tax rate deduction, etc. a field is a meaningful collection of related characters. It is the smallest logical data entity treated  as a single unit in data processing. Note that a field any sometimes have a single character, such as sex-code field may have value M or F.

4. Record: A record is combination of multiple related fields. For example, an employee record has fields containing data of an employee, such as employees' code, name, worked hours, pay rate, tax rate deduction, etc. Similarly, a student record has fields containing data of a student. Hence, A record is a collection of related fields, which data processing applications treat as a single unit. 

5. File: A file is a combination of multiple related records. For example, a collection of employees records of a company forms an employee file. Similarly, a collection of all Inventory records of a company forms an inventory file. Hence , a file is a number of related records, which the system treats as a unit. Notice that every record in a file has the same set of fields. A key field uniquely identifies each record in a file. Contents of the field are unique for every record in the file. For an employee file, employee-code field may serve as the key field.

6. Database: A database is an integration of multiple related files. For example, an employee database of an organisation may integrate records of multiple files, such as employee salary file containing details of salary and taxation information of all employees, and employee personal information file containing general information ( age, sex, address, etc.) of all employees, and employee skill set file containing details of various types of skills of all employees. 

A database integrates data from multiple files in a manner of minimize data redundancy. For instance, in case of employee above of three different employee files, if in each file an employee record contains an employee address field, and if an employee changes his/her residence, the organisation must change the employees' address in all three files. A database requires change in the employees' address data only once and make the same copy available to all applications. In essence, a database is a collection of a logically related data elements from multiple files.