ORGANISING DATA

DATA AS ORGANISATIONAL RESOURCE 

Before the computer came into existence, there were many limitations associated with the physical handling of documents and human processing. Computers came into existence to speed up the data processing. Computers helped to manage data. 

We are living in the age of information processing. The ability to acquire accurate and timely data, managing data efficiently, is all through which an organization succeed. 

The development in hardware has catalysed rapid development in software and now we are having more sophisticated software to handle data as it was earlier.

The term data and information are often taken as to mean the same thing. Data are the details about factories, outlets, staff, competitors, customers and suppliers. Data is also kept for monitoring the activities and processes in business. Once businesses collect these details, information comes into picture. Information is the collection of meaningful facts that are derived from the data. Information is significant and relevant to the user unlike data, which has no meaning alone. Information leads to decision and thus an appropriate action. In fact, information consists of only the data that is useful, meaningful and needed. You come across many information systems in your daily life like banking information system, ticketing and reservations systems etc. Now what you get out of these information systems is pure information and these systems work out this information on the basis of data. In other words, data is raw and information is refined. The exact form of the refinement depends on the type of application one is dealing with. 

The data must be accurate, timely and relevant. It is desired that any information system should have accurate data to work on. Inaccurate data howsoever well analysed will hardly be useful for any decision-making. Although collection of accurate data is costly and time consuming, every effort should be made to make it as accurate as possible. One may strike a balance between the cost of processing and value of accuracy. The data should also be timely. If the right data is not available at the right time then it is worth little use. For example if the updating of electoral lists cannot take place before the schedule of elections then it is of no use to the elections. The timeliness of the data is detrimental of success of any information system. The data should be relevant. For better understanding of the organizations and their information needs data has to be high on the relevance factor. There are many Decision-Support Systems (DSS) and Executive Support Systems that are present in today’s scene, but the general feeling is that often the data is generating accurate and timely information, that is not very relevant. However, the future looks bright because of the emergence of high-end computing machines, sophisticated data capturing devices and other technology driven tools. Technology is making data available in larger quantities than ever before, due to lower cost storage, increased processing speeds, higher capacity communications and increased variety of information formats. 

ORGANISING DATA

In earlier times, data processing was done manually. Organizations appoint a large number of people called clerks. The information technology devices used at that time was forms, ledger books and basic mechanical adding machines. The results of such manual operations were obtained at a time when the information was almost out of date (e.g. census). Then some systems were invented in which processing was mostly mechanized e.g. Hollerith Tabulation System. In such systems data was recorded in the binary form of holes in cards, using a cardpunch. These stacks of cards could be sorted and tabulated. IBM and Remington Rand led the development of punched card technology. 

Things have changed considerably with the advent of computers. There are a few terms that you need to know about the data organization. IT-specific encyclopaedia of whatis.techtarget.com and searchdatabase.com defines theses terms as follows: 

Bit: A bit (short for binary digit) is the smallest unit of data in a computer. A bit has a single binary value, either 0 or 1. Although computers usually provide instructions that can test and manipulate bits, they generally are designed to store data and execute instructions in bit multiples called bytes. In most computer systems, there are eight bits in a byte. 

Byte: In most computer systems, a byte is a unit of data that is eight binary digits long. A byte is the unit most computers use to represent a character such as a letter, number, or typographic symbol (for example, “g”, “5”, or “?”). A byte can also hold a string of bits that need to be used in some larger unit for application purposes. 

Field: A field is an area in a fixed or known location in a unit of data such as a record, message header, or computer instruction that has a purpose and usually a fixed size. In some contexts, a field can be subdivided into smaller fields. In a database table, a field is a data structure for a single piece of data. Fields are organized into records, which contain all the information within the table relevant to a specific entity. For example, in a table called customer contact information, telephone number would likely be a field in a row that would also contain other fields such as street address and city. The records make up the table rows and the fields make up the columns. 

Record: In a database, a record (sometimes called a row) is a group of fields within a table that are relevant to a specific entity. For example, in a table called customer contact information, a row would likely contain fields such as: ID number, name, street address, city, telephone number and so on. 

File: In data processing, using an office metaphor, a file is a related collection of records. For example, you might put the records you have on each of your customers in a file. In turn, each record would consist of fields for individual data items, such as customer name, customer number, customer address, and so forth. 

Database: A database is a collection of information that is organized so that it can easily be accessed, managed, and updated. In one view, databases can be classified according to types of content: bibliographic, full-text, numeric, and images.

In relation to database, an entity means a person, place, or thing that we wish to collect information on (e.g. customers). The word root is from the Latin, ens, or being, and makes a distinction between a thing’s existence and its qualities. Attribute is a characteristic of an entity (e.g. customer’s salary, customer’s address). 

In a Database Management System (DBMS), an attribute may describe a component of the database, such as a table or a field, or may be used itself as another term for a field. Key Field is a special field that uniquely identifies a single record (e.g. customer’s registration number). It can be a collection of fields. 

In a database management system (DBMS), files are either organised sequentially (one record after another, used for batch processing) or organised in an indexed sequential form (in sequence, but records can be directly accessed using an index) or in the form of direct or random form (records located using a key field generated by a mathematical formula.)