Basic Terminology: Elementary Data Organization:

Basic Terminology: Elementary Data Organization:

1. Data: Data are simply values or sets of values.

2. Data items: Data items refers to a single unit of values.

Data items that are divided into sub-items are called Group items. Ex: An Employee Name may be divided into three subitems- first name, middle name, and last name.

Data items that are not able to divide into sub-items are called Elementary items.

Ex: SSN

3. Entity: An entity is something that has certain attributes or properties which may be assigned values. The values may be either numeric or non-numeric.

Ex:         

Attributes-

Names,

Age,

Sex,

SSN

Values-

Rohland Gail,

34,

 F,

134-34-5533

Entities with similar attributes form an entity set. Each attribute of an entity set has a range of values, the set of all possible values that could be assigned to the particular attribute.

The term “information” is sometimes used for data with given attributes, of, in other words meaningful or processed data.

4. Field is a single elementary unit of information representing an attribute of an entity.

5. Record is the collection of field values of a given entity.

6. File is the collection of records of the entities in a given entity set. 

Each record in a file may contain many field items but the value in a certain field may uniquely determine the record in the file. Such a field K is called a primary key and the values k1, k2, ….. in such a field are called keys or key values.

  • Records may also be classified according to length.

A file can have fixed-length records or variable-length records.

  • In fixed-length records, all the records contain the same data items with the same amount of space assigned to each data item.
  • In variable-length records file records may contain different lengths.

Example: Student records have variable lengths, since different students take different numbers of courses. Variable-length records have a minimum and a maximum length.

The above organization of data into fields, records and files may not be complex enough to maintain and efficiently process certain collections of data. For this reason, data are also organized into more complex types of structures.

  • The study of complex data structures includes the following three steps:

1. Logical or mathematical description of the structure

2. Implementation of the structure on a computer

3. Quantitative analysis of the structure, which includes determining the amount of memory needed to store the structure and the time required to process the structure.

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