Understanding Data Warehousing and Data Mining In a Simplified Way
Data Warehousing and Data Mining Homework Help are the basis of the transformation of data to knowledge. To help you get a better understanding of this topic we are dividing the topic into two parts:
Data is the raw of information which is processed to be converted into meaningful information. It is used in all organisations and institutes which deals with a large load of data and information.
Data Warehousing is the process of constructing then using a warehouse of data. The data warehouse is constructed through the integrated efforts of data integration, data cleaning and data consolidation. The data warehouse so constructed is done with the help of collection of data from different sources.
A data warehouse is constructed through the means of using two approaches. They are:
In Query driven Approach, the data is collected from sources with the help of questionnaires, check lists and census. This is the traditional method of data collection. It is a labour intensive approach as the data needs to be processed locally before being integrated with the data warehouse.
In this Approach of data collection, the entire database from different sources is integrated in advance. The data is not processed locally but integrated at once to be analysed later. This is the modern approach and faster compared to Query Driven Approach.
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Data Warehousing and Data Mining Homework Help is the basis of all databases. Data Mining focuses on the extraction of information from the pile of raw data. It is the process of identifying a pattern or algorithm in large volumes of data and information. This is done to ease the tedious task of segregating data into meaningful databases.
There are a number of techniques which are used for the process of Data Warehousing and Data Mining Homework Help. They have been enumerated below:
In this technique, you have the simple task of identifying a similarity or correlation between the data items.This is the simplest and more frequently used data mining technique.
In this data mining technique, the data items are segregated into different categories. The categories are formed based on the defining characteristic of the data items. After Association, you have to distribute the data items having similar characteristics into classified categories.
Using probability and behaviour pattern, data items are segregated based on prediction. These predictions study the past events and situations to predict the future movement of the data items.
Hence, there are a number of techniques to ensure efficient segregation of data in Data Warehousing and Data Mining Assignment Help. To study more about this topic visit myhomeworkhelp.com.
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