Call for Paper - August 2022 Edition
IJCA solicits original research papers for the August 2022 Edition. Last date of manuscript submission is July 20, 2022. Read More

Improvement of Query Processing Speed in Data Warehousing with the Usage of Components-Bitmap Indexing, Iceberg and Uncertain Data

Print
PDF
International Conference on Current Trends in Advanced Computing (ICCTAC-2015)
© 2015 by IJCA Journal
ICCTAC 2015 - Number 1
Year of Publication: 2015
Authors:
Uma Pavan Kumar
Lakshma Reddy
Sreedevi. S. Erady

Uma Pavan Kumar, Lakshma Reddy and Sreedevi.s.erady. Article: Improvement of Query Processing Speed in Data Warehousing with the Usage of Components-Bitmap Indexing, Iceberg and Uncertain Data. International Conference on Current Trends in Advanced Computing (ICCTAC-2015) ICCTAC 2015(1):27-31, May 2015. Full text available. BibTeX

@article{key:article,
	author = {Uma Pavan Kumar and Lakshma Reddy and Sreedevi.s.erady},
	title = {Article: Improvement of Query Processing Speed in Data Warehousing with the Usage of Components-Bitmap Indexing, Iceberg and Uncertain Data},
	journal = {International Conference on Current Trends in Advanced Computing (ICCTAC-2015)},
	year = {2015},
	volume = {ICCTAC 2015},
	number = {1},
	pages = {27-31},
	month = {May},
	note = {Full text available}
}

Abstract

Data warehousing is a huge collection of data sources meant for handling strategic decisions with historical and current data. The recent trend in information technology market is big data analytics. Huge amounts of data available with the companies but the proper information as per the requirements is still a challenging issue. The current article is dealing with the implementation of iceberg queries, slowly changing dimensions and uncertain data processing. The idea behind the integration of these aspects is processing subsets of the data from the huge amounts of the data. In case of iceberg querying the main theme is aggregate query processing such as count, sum, average, maximum and minimum kind of calculations. In most of the cases the analysis of the data and comparison of the performance aspects between aggregations only, so usage of iceberg querying will improve the processing speed of the data warehousing. The second component we are considering to process data warehousing is slowly changing dimensions. The dimension tables are the basic things of the data warehousing construction, usually dimensions will change slowly not frequently. If we are able to track the changes done to the dimensions such as maintenance of historical and current data, with the tracking of data we can get the subset of data which got modified or which we need to process, which will greatly reduce the number of records to process. The third component we are considering is uncertain data processing. The data which is not having any structure and no information about the format is known as uncertain data, now a days the data population of the data like reviews, likes or shares in social media, MS response all are recorded in uncertain format. The processing of uncertain data with softest computing will give the identification of missing data, parameterization aspects are possible.

References

  • Bhosale"Efficient Indexing Techniques on Data Warehousing" International Journal of Scientific & Engineering Research vol 4, Issue 5, May-2013, ISSN 2229-5518.
  • NaveenGar,PhDscholar,SNUniversity,Jharkhand,"Bitmap Indexing technique for data warehousing and data mining", International Journal of Latest trends in engineering& Technology vol 2. Issue 1,January 2013,ISSN:2278-621X
  • Zanab qays abdulhadi, school of information systems and engineering, central south university, china. "Bitmap index as effective indexing for low cardinality column in data warehouse", International Journal of computer applications, vol 68, April 2013, ISSN: 0975-8887).
  • Jesus Camacho- Rodriguez "Web data indexing in the cloud: Efficiency and Cost reductions", ©ACM 2013, March 18-22.
  • Naveen Garg, PhD Scholar, "An Efficient Approach for data indexing in DWH&DM", International Journal of Innovations in engineering and Technology, vol-1, Issue 4, Dec 2012.
  • Biyramjit paul, Asst. Prof Dept. of CA,Westbengal "Comparative study of various Bitmap Indexing techniques used in Data warehouse" , ,International Journal of Emerging trends & Technology in computers,ISSN 2278-6856,Vol-1,Issue-3,Sep-2012.
  • Amorntep Keawpibal "Enhanced Encoded Bitmap Index For equality Query", Thailand, IEEE, 2012.
  • T. P. Latchoumi, "Multi Agent Systems In Distributed Data warehousing", International Conf. on Computer & Communication Technology
  • Andrea Campagna,"Frequent Pairs in Data Streams: Exploiting Parallelism and Skew", 2011 11th IEEE International Conference on Data Mining Workshops
  • Gehad Galal ,"Exploiting Parallelism in Knowledge Discovery Systems to Improve Scalability", ,1060-3425/98 (c) 1998 IEEE
  • Marco Vieira, Henrique Madeira" Integrating GQM and Data Warehousing for the Definition of Software Reuse Metrics", ,2011 34th IEEE Software Engineering Workshop
  • Munawar " Towards Data Quality into the Data Warehouse development", 2011 Ninth IEEE International Conference on Dependable,
  • Abdolreza Hajmoosaei, "Autonomic and Secure Computing978-0-7695-4612-4/11© 2011 IEEEDOI 10. 1109/DASC. 2011. 1941200-2011 IEEE Ninth International Conference on Dependable,
  • COMPARISON PLAN FOR DATAWAREHOUSE SYSTEM ARCHITECTURES Data sheet© 2011 Microsoft Corporation
  • Satkaur , Research scholar, S. K. I. E. T. ,Kurukshetra, Haryana "International Journal of Advanced Research in computer Science and Software Engineering" , , Volume 3, Issue 5, May 2013 ISSN: 2277 128X .
  • Jens Dittrich JorgeArnulfo,Quian´eRuizInformation Systems Group Saarland University "Efficient Big Data Processing in Hadoop Map Reduce, Proceedings of the VLDB Endowment", Vol. 5, No. 12Copyright 2012 VLDB
  • Lizhe Wang, School of Computer, China University of Geosciences, "G-Hadoop: Map Reduce across distributed data centers for data-intensive computing, Future Generation Computer Systems", the international journal of grid computing and esciences 2012 Elsevier.
  • Bo Dong, Department of Computer Science and Technology, Xi'an Jiaotong University, Xi'an, China, "A Novel Approach to Improving the Efficiency of Storing and Accessing Small Files on Hadoop: a Case Study by PowerPoint Files", , 2010 IEEE International Conference on Services Computing.
  • Muhammad Inayat Ullah, Gomal University, "Transformation of Flat File into Data Warehouse", Global Journal of Computer Science and Technology, Volume 11 Issue 13 Version 1. 0 August 2011.
  • Sheetal ganu, Punjabi university, "Improved Extraction mechanism in ETL process for building of a Data Warehouse", IEEE international conference, Mumbai.
  • Ranjit Singh, Research Scholar, University College of Engineering (UCoE), Punjabi University, "A Descriptive Classification of Causes of Data Quality Problems in Data Warehousing", IJCSI International Journal of Computer Science Issues, Vol. 7, Issue 3, No 2, May 2010 41ISSN (Online): 1694-0784
  • Md AL Mamun, "Performance improvement techniques for customized data warehouse", IOSR-JCE, April 2013.
  • Bin He "Efficient Iceberg query evaluation using compressed bitmap index", , IEEE Transactions,Sept,2012
  • Chuyang Wei, "Efficient Cube computing on an extended multi-dimensional model over uncertain data," IEEE 2012
  • http://www. tgc. com/dsstar/01/0109/102533. html