A data dictionary contains a set of precise and accurate definitions of all DFDs, data elements and data structures.
The following rules are followed in constructing a data dictionary:
a) The terms used to describe data structures are always in capital letters.
b) Multiple word names are hyphenated.
c) Names assigned should be straight forward and user-oriented.
d) There should [...]

Data couple carries data between two modules and it can have upward or downward direction. Data flows are depicted using named arrows with a small circle at one end. But control couple only carries information about data couple and does not carry any data.
Control couple is always directed upwards because it shows the module which [...]

You can  change your Oracle login password using  the Change Password page. Changing your password regularly reduces the risk of someone obtaining your password and gaining unauthorized access to your account. You must specify your username, old password, and your new password (twice). In SQL*Plus, you can change your password by using the SQL*Plus PASSWORD [...]

Executing a script and formatting its output are controlled by system variables. A system variable  in iSQL*Plus is similar to a variable in any programming language. Like a column in a row of a table, a system variable can hold a string or a number. The string or number in the system variable controls some [...]

NULL value in an Oracle table is nothing. A NULL is neither zero, a blank character, or an empty string.  NULLs can be the source of much consternation when a query is not returning the expected results.
NULL :- A possible value for any Oracle column that indicates the absence of any known value for that [...]

Because Oracle SQL is table-centric, most operations performed with SQL must reference some kind of table or view. For example, consider the following SQL statement:
       SELECT NAME;
       SELECT NAME
                 *
       ERROR at line 1:
       ORA-00923: FROM keyword not found where expected

This returns an error, because the basic syntax of a SELECT statement requires that [...]

Most banks and financial institutions offer a wide variety of banking services (for example saving balance checking, individual transactions), credit (such as loans, mortgage) and investment services (mutual funds). Some also offer insurance services and stock investment services.
Financial data collected in the banking and financial i9ndustry are often relatively complete,reliable and of high quality,which facilities [...]

Clustering is a division of data into groups of similar objects. Each group, called cluster, consists of objects that are similar between themselves and dissimilar to objects of other groups. Representing data by fewer clusters necessarily loses certain fine details (akin to lossy data compression), but achieves simplification. It represents many data objects by few [...]

Sometimes, a simple GROUP BY clause just isn’t enough in a query. Once you generate a report of, let’s say, average salary by department or the standard deviation of sick days by job title, you often must run a second query that calculates the average salary or standard deviation across the [...]

Data mining has many and varied fields of application some of which are listed below.
Retail/Marketing
1. Identify buying patterns from customers
2. Find associations among customer demographic characteristics
3. Predict response to mailing campaigns
4. Markets analysis
Banking
1. Detect patterns of fraudulent credit card use
 2. Identify ‘loyal’ customers
3. Predict customers likely to change their credit card affiliation
4. Determine credit card [...]

1.Growing Data Volume
The main reason for necessity of automated computer systems for intelligent data analysis is the enormous volume of existing and newly appearing data that require processing. The amount of data accumulated each day by various business, scientific,and governmental organizations around the world is daunting.
2. Limitations of Human Analysis
Two other problems that surface when [...]

There are many data mining systems available or being developed. Some are specialized systems dedicated to a given data source or are confined to limited data mining functionalities, other are more versatile and comprehensive.
1. Classification according to the type of data source mined:  this classification categorizes data mining systems according to the type of data [...]

The kinds of patterns that can be discovered depend upon the data mining tasks employed. By and large, there are two types of data mining tasks: descriptive data mining tasks that describe the general properties of the existing data, and predictive data mining tasks that attempt to do predictions based on inference on available data. [...]

In principle, data mining is not specific to one type of media or data. Data mining should be applicable to any kind of information respiratory. However, algorithms and approaches may differ when applied to different types of data. Indeed, the challenges presented by different types of data very significantly. Data mining is being put into [...]

A database management system (DBMS) is a collection of interrelated data and a set of programs to access the data. The collection of data, usually referred to as the database, contains information related to an enterprise. The primary goal of a DBMS is to provide a way to store and retrieve database information that is [...]