Open Access Open Access  Restricted Access Subscription or Fee Access

Data Warehouse Development Based on Cloud Computing Using IBM Informix and IBM Cognos for Multifinance Industry


(*) Corresponding author


Authors' affiliations


DOI: https://doi.org/10.15866/irecos.v11i9.10070

Abstract


The purpose of this research is to design a cloud-based data warehouse system based on cloud computing in the multi finance industry, especially on the subject of sales area aimed at improving the operational performance of the system. There are two software used in designing a data warehouse system: IBM Informix Warehouse Feature Design Studio which is used for Extract, Transform, and Load (ETL) process and IBM Cognos Report Studio which is used for dashboard report sales area. The research methodology of this research is as follows: analysis through literature review, interviews, and observations. The data warehouse was designed using Ralph Kimball’s 9 stage of designing the data warehouse. The output of this research is a product of cloud-based data warehouse system that can be used by the finance industry on the sales subject area.
Copyright © 2016 Praise Worthy Prize - All rights reserved.

Keywords


Data Warehouse; Cloud Computing; Multi-Finance; IBM Informix; IBM Cognos

Full Text:

PDF


References


Goswami, V., Patra, S. S., and Mund, G. B., Optimal Management of Cloud Centers with Different Arrival Modes for Cloud Computing Environment, International Journal of Cloud Applications and Computing, Vol. 2, n. 3, pp. 86-97, 2012.
http://dx.doi.org/10.4018/ijcac.2012070104

Gandhi, V. C., Prajapati, J. A., and Darji, P. A., Cloud Computing with Data Warehousing, International Journal of Emerging Trends & Technology in Computer Science, Vol. 1, n. 3, pp. 72-73, 2012.
http://dx.doi.org/10.18535/ijetst/v3i04.01

Aljabre, A., Cloud Computing for Increased Business Value. International Journal of Business and Social Science, Vol. 3, n.1, pp. 234-239, 2012.
http://dx.doi.org/10.1002/9781119204732.ch16

Inmon, W.H., Hackathorn, and R.D., Using the data warehouse. (Somerset: Wiley-QED Publishing, 1994).
http://dx.doi.org/10.1016/b978-0-12-408067-6.00016-4

Jindal, R., & Taneja, S., Comparative Study Of Data Warehouse Design Approaches: A Survey. International Journal of Database Management Systems ( IJDMS ), Vol. 4, n. 1, pp. 33-45, 2012
http://dx.doi.org/10.5121/ijdms.2012.4104

W. H. Inmon, Building the Data Warehouse. (New York: John Wiley Sons Inc., 2005).
http://dx.doi.org/10.1002/div.2085

Ouf, S., & Nasr, M. The Cloud Computing: The Future of BI in the Cloud. International Journal of Computer Theory and Engineering. Vol. 3, n. 6, pp. 750-754, 2011.
http://dx.doi.org/10.7763/ijcte.2011.v3.404

Williams, B. K., & Sawyer, S. C., Using Information Technology. (New York: McGraw-Hill, 2011).
http://dx.doi.org/10.1126/science.133.3450.374

Connolly, T. M., & Begg, C. E., Database Systems A Practical Approach to Design, Implementation, and Management (Harlow: Pearson Education Limited, 2005).
http://dx.doi.org/10.1002/9780470602379.ch3

O'Brien, J. A., & Marakas, G. M., Introduction to Information Systems. (New York: McGraw-Hill/Irwin, 2010).
http://dx.doi.org/10.1145/382072.1037786

Kimball, R., Ross, M., Thornthwaite, W., Mundy, J., & Becker, B., The Data Warehouse Lifecycle Toolkit (Indianapolis: Wiley, 2008).
http://dx.doi.org/10.1145/945721.945741

Gour, V., Sarangdevot, S. S., Tanwar, G. S., & Sharma, A., Improve Performance of Extract, Transform and Load (ETL) in Data Warehouse. International Journal on Computer Science and Engineering, Vol. 2, n. 3, pp. 786-789, 2010.
http://dx.doi.org/10.5120/623-887

Reddy, G., Srinivasu, R., M., P. C., & Rikkula, S. R., Data Warehousing, Data Mining, OLAP, and OLTP Technologies are Essential Elements to Support Decision-Making Process in Industries. International Journal of Computer Science and Engineering. Vol. 2, n. 9, pp. 2865-2873, 2010.
http://dx.doi.org/10.1201/9781420049145.ch11

Barathi, K. K., & Sree, K. S., Recent Developments on Data Warehouse and Data Mining In Cloud Computing. International Journal of Computer Science Engineering and Technology (IJCSET), Vol. 5, n.2, pp. 31-34, 2015
http://dx.doi.org/10.18535/ijecs/v5i4.01

Gandhi, V. C., Prajapati, J. A., and Darji, P. A.. Cloud Computing with data warehousing and Analysis Market June 2009. International Journal of Emerging Trends & Technology in Computer Science (IJETTCS), Vol. 1, n. 3, 2012
http://dx.doi.org/10.1109/icrtit.2012.6206752

Reynaud, C., Pernelle, N., & Rousset, M., Data Extraction, Transformation and Integration Guided by an Ontology. International Journal of Data Warehousing Design and Advanced Engineering Applications: Methods for Complex Construction, Vol. 1, n. 6, pp. 17-37, 2012
http://dx.doi.org/10.4018/978-1-60566-756-0.ch002

Verma, H., Data-warehousing on Cloud Computing. International Journal of Advanced Research in Computer Engineering & Technology (IJARCET), Vol. 2, n. 2, 2013
http://dx.doi.org/10.2991/icacsei.2013.152

Wilder, B., Cloud Architecture Patterns (Sebastopol: O'Reilly Media, 2012).
http://dx.doi.org/10.7771/2380-176x.4851

Cognos Business Intelligence and Enterprise Performance Management, Retrieved September 13, 2016, from http://www.cognos-bi.info/
http://dx.doi.org/10.1145/1923947.1923986

Kirankumar, G., Sunil, K. J., Avinash, R. K., Analysis of Using a Business Intelligence Tool (COGNOS) in a Company to Result in More Efficient and Intuitive Company in the Current Era. Business Intelligence Journal, Vol. 5, n.2, 2012
http://dx.doi.org/10.1002/cir.3880020209

Nabri, H., Ouazar, D., Hasnaoui, M., Spatial Data Warehouse Modeling at the Watershed Scale. Part 1: Design Aspects, (2015) International Journal on Information Technology (IREIT), 3 (4), pp. 124-130.


Refbacks

  • There are currently no refbacks.


Please send any question about this web site to info@praiseworthyprize.com
Copyright © 2005-2024 Praise Worthy Prize