Getting to know Data Mining Analysis Better

by admin on August 26, 2011

Getting to know Data Mining Analysis Better

Data Mining, in general terms is also known as data discovery or fact search. Add analysis to that phrase, and you have the process changing completely, to becoming analysis of data from different perspectives. In the end, it gets summarized into useful and benefitting information. Data Mining Analysis is one of the most important parts of Marketing Segmentation, helping in finding out correlations amongst plenty of fields in relational databases.


How does Data Mining Analysis work?


Data Mining Analysis helps analyze the link between large scale information technology involving distinct transaction and analytical systems. The analysis process helps understand relationships and patterns better. It is used extensively in marketing segmentation, especially with all the minute nuances and factors to be clearly understood.


Data Mining Analysis is often performed on classes, clusters, associations and sequential patterns. The data stored is used for locating in predetermined groups. The items get grouped in accordance with logical relationships and consumer preferences. Market segments and consumer affinities are identified through these clearly. In marketing segmentation, the mining of data helps anticipate behavioral patterns.


The mining part comprises of 5 major elements:


ü  Extraction, transformation and transaction of data onto the warehouse systems.

ü  The storage and management of data in a multidimensional database system.

ü  Access to business analysis, and information technology.

ü  Analysis through application software.

ü  Presentation in a very useful and cohesive format.


Data Mining Analysis in Marketing Segmentation is done at different levels:


ü  Artificial Neural Networks: This stage has non linear predictive models learning through training and striking and a resemblance to structural biological neural networks.


ü  Genetic Algorithms: These have optimization processes making use of techniques like genetic combination, mutation, natural selection in a design completely modelled on concepts related to natural evolution.

ü  Decision Trees: In marketing segmentation, decision trees are reference to sets of decisions. These ones are meant to generate rules to classify datasets. They include the likes of Classification and Regression Trees, Cho Square Automatic Interaction Detection. They help classify datasets. The set of rules can be used to predict record with an outcome. The method helps create two way splits, and multi way splits also.

ü  Rule Induction: The extraction of data at this level happens thoroughly on the basis of statistical significance.

ü  Data Visualization: This level has a lot of visual interpretations of complex relationships in multidimensional data. Data relationships are illustrated through the help of graphic tools.

ü  The Nearest Neighbour Method: This is a technique broadly used in marketing segmentation, to help classify records in a dataset based on combinations of classes similar to historical datasets.

Data Mining Analysis is accrued huge importance to in business market intelligence. The fact such delicate data is at hand to be analyzed, and has to be thoroughly studied through various sets of advanced statistical tools only accentuates the case proper mining. The vendor doing this carries the onus of ensuring the data is accurate to the core, and its veracity verified.


The process is easier provided looked at from close quarters.

data visualization

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