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DESIGN AND DEVELOPMENT OF DATA MARTS FOR HOUSEHOLD AMENITIES FROM CENSUS DATA (MAHARASHTRA)

KrishiKosh

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Title DESIGN AND DEVELOPMENT OF DATA MARTS FOR HOUSEHOLD AMENITIES FROM CENSUS DATA (MAHARASHTRA)
 
Creator RAMDASI SANMIT SURESH
 
Contributor S. D. Sharma
 
Subject ---
 
Description t-8060
In India, the agricultural resources are spread across the nation. Therefore, the first and
foremost need for developing a decision support system on agriculture resources is to
integrate the scattered historical information into a central data warehouse. Integrated
National Agricultural Resources Information System (INARIS), which is developed by
IASRI, New Delhi, is an endeavor in developing a central information repository of
major agricultural resources.
By keeping the above need in mind the available data from census of India 2001,
regarding the Household Amenities in Maharashtra State have been analyzed to identify
possible data marts and the dimensions that can be associated with these data marts. To
find out the associated dimensions with the data marts and conformed dimensions, the
top-down planning approach called as Data Warehouse Bus Architecture Matrix was
used. With the help of this matrix the dimensional models have been designed and
subject wise data marts are created. The data storage has been converted into a form of
multidimensional model, known as cube. These cubes have been designed by using fact
and dimension tables and deployed on Internet for on-line analysis, which is called as
On-Line Analytical Processing (OLAP). The cubes have been integrated with previously
developed data warehouse INARIS. The information in this data warehouse is available
to the end-user in the form of decision support system in which all the flexibility of the
presentation of the information, such as it’s on line analysis is inbuilt into the system.
The data in the developed cubes can be viewed in cross tab view as well as graphical
views including simple bar graph, pie chart, clustered bar graph, stacked bar graph,
multiline graph, three dimensional bar graph etc. Drill downs and roll ups can be
performed on the data available in the cubes. Another important functionality
incorporated in these cubes is Drill Through in which user can find interesting trends or
anomalies while analyzing data. The advantage of this approach is that the often queryintensive
work of ad hoc data analysis is performed using summarized data in t
 
Date 2016-12-27T15:28:35Z
2016-12-27T15:28:35Z
2009
 
Type Thesis
 
Identifier http://krishikosh.egranth.ac.in/handle/1/93280
 
Format application/pdf