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Prediction of Data Ware House Model using Dynamic Function Point Analysis

K. Bhuvaneswari1

Section:Research Paper, Product Type: Journal Paper
Volume-07 , Issue-04 , Page no. 47-51, Feb-2019

Online published on Feb 28, 2019

Copyright © K. Bhuvaneswari . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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IEEE Style Citation: K. Bhuvaneswari , “Prediction of Data Ware House Model using Dynamic Function Point Analysis,” International Journal of Computer Sciences and Engineering, Vol.07, Issue.04, pp.47-51, 2019.

MLA Style Citation: K. Bhuvaneswari "Prediction of Data Ware House Model using Dynamic Function Point Analysis." International Journal of Computer Sciences and Engineering 07.04 (2019): 47-51.

APA Style Citation: K. Bhuvaneswari , (2019). Prediction of Data Ware House Model using Dynamic Function Point Analysis. International Journal of Computer Sciences and Engineering, 07(04), 47-51.

BibTex Style Citation:
@article{Bhuvaneswari_2019,
author = {K. Bhuvaneswari },
title = {Prediction of Data Ware House Model using Dynamic Function Point Analysis},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {2 2019},
volume = {07},
Issue = {04},
month = {2},
year = {2019},
issn = {2347-2693},
pages = {47-51},
url = {https://www.ijcseonline.org/full_spl_paper_view.php?paper_id=719},
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
UR - https://www.ijcseonline.org/full_spl_paper_view.php?paper_id=719
TI - Prediction of Data Ware House Model using Dynamic Function Point Analysis
T2 - International Journal of Computer Sciences and Engineering
AU - K. Bhuvaneswari
PY - 2019
DA - 2019/02/28
PB - IJCSE, Indore, INDIA
SP - 47-51
IS - 04
VL - 07
SN - 2347-2693
ER -

           

Abstract

Approach for estimation of Data Ware House(DWH) Projects/Data Marts using Function Point Analysis is an ETL Development, Enterprise. The Objectives are the burden of maintaining the composite and enterprise data model by the data warehouse is not directly recognized. Often a development team’s “hidden” efforts in delivering the support architecture of a data warehouse are compared unfavorably with more traditional, and highly visible, user functionality. Unlike other traditional data base systems, a Data Warehouse uses other software systems as data sources and does not create new information, which generally would be more static in nature. So, applying Function Point Analysis to Data warehouse applications became more tedious as Data warehousing itself has some peculiarities of its own compared to traditional OLTP(Online Transactional Processing) applications. Data Warehouse/Data Mart are a special type of applications, with particular characteristics such as the fact that the users only use the software system for queries and report generation and not for data update, the fact that development is based on existing data of other systems without generating new information, and the fact that it follows a different development process than the traditional OLTP software systems. It is necessary, therefore, to adapt (rather than to exactly follow) the size measurement approach defined for the traditional OLTP systems so that they consider the specific characteristics of Data warehouse/Data Mart and generate more accurate estimations. The proposed approach helps in estimating Data warehouse/Data Mart Projects using Function Point Analysis especially for ETL operations, in a more traditional and systemati c way.

Key-Words / Index Term

FPA - Function Point Analysis, OLAP - Online Analytical Processing, ETL - Extraction, Transformation, Loading, OLTP - Online Transactional Processing, DWH - Datawarehouse

References

[1]. INMON, W.H., Definition of a Data Warehouse.1999.
[2]. KIMBALL, R.,THORNTHWAITE, W.,REEVES, L..ROSS, M.,The Data Warehouse Lifecycle Toolkit.
[3]. New York: John Wiley & Sons, 1998. FENTON,N., PFLEEGER, S. Software Metrics A Rigorous & Practical Approach. Boston: PWS Publishing Company, 1997.
[4]. ISO/IEC 9126:2001.Software engineering Product quality.2001.
[5]. IFPUG. International Function Point Users Group. Function Point Counting Practices Manual: Release 4.1. Ohio: IFPUG. 2000.
[6]. Adapting function point analysis to estimate data mart size by Angelica ToffanoCalazans, MarcalDe Oliveira, RildoRibeiroDos Santos.