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Reduce The Wastage of Data During Movement in Data Warehouse

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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2016
Authors:
Ahmed Mateen, Lareab Chaudhary
10.5120/ijca2016911907

Ahmed Mateen and Lareab Chaudhary. Reduce The Wastage of Data During Movement in Data Warehouse. International Journal of Computer Applications 152(8):20-24, October 2016. BibTeX

@article{10.5120/ijca2016911907,
	author = {Ahmed Mateen and Lareab Chaudhary},
	title = {Reduce The Wastage of Data During Movement in Data Warehouse},
	journal = {International Journal of Computer Applications},
	issue_date = {October 2016},
	volume = {152},
	number = {8},
	month = {Oct},
	year = {2016},
	issn = {0975-8887},
	pages = {20-24},
	numpages = {5},
	url = {http://www.ijcaonline.org/archives/volume152/number8/26340-2016911907},
	doi = {10.5120/ijca2016911907},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}
}

Abstract

In this research paper so as to handle Data in warehousing as well as reduce the wastage of data and provide a better results which takes more and more turn into a focal point of the data source business. Data warehousing and on-line analytical processing (OLAP) are vital fundamentals of resolution hold, which has more and more become a focal point of the database manufacturing. Lots of marketable yield and services be at the present accessible, and the entire primary database management organization vendor nowadays have contributions in the area assessment hold up spaces some quite dissimilar necessities on record technology compare to conventional on-line transaction giving out application. This article gives a general idea of data warehousing and OLAP technologies, with the highlighting on top of their latest necessities. So tools which is used for extract, clean-up and load information into back end of a information warehouse; multidimensional data model usual of OLAP; front end client tools for querying and data analysis; server extension for proficient query processing; and tools for data managing and for administration the warehouse. In adding to survey the circumstances of the art, this article also identify a number of capable research issue, a few which are interrelated to data wastage troubles. In this paper use some new techniques to reduce the wastage of data, provide better results. In this paper take some values, put in anova table and give results through graphs which shows performance.

References

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Keywords

Data warehouse, IO, OLAP, analytical, Hadoop, volume, velocity, variety, function, Big Data.