International Journal of Computer
Trends and Technology

Research Article | Open Access | Download PDF

Volume 67 | Issue 9 | Year 2019 | Article Id. IJCTT-V67I9P113 | DOI : https://doi.org/10.14445/22312803/IJCTT-V67I9P113

Data Warehouse Architecture – Leading the next generation Data Science

Rahul Reddy Nadikattu

Citation :

Rahul Reddy Nadikattu, "Data Warehouse Architecture – Leading the next generation Data Science," International Journal of Computer Trends and Technology (IJCTT), vol. 67, no. 9, pp. 78-80, 2019. Crossref, https://doi.org/10.14445/22312803/ IJCTT-V67I9P113

Abstract

The present study emphasizes the importance of the data warehouse as an important tool to maintain both ancient and present data, The study provides insight into the significant components of data warehouse architecture with its specific usage in the information science domain. In recent year ears, there has been a rapid expansion of the applicative properties of data warehousing owing to its wage in mobile and other social media platforms, In the current scenario, there has been a gradual shift in big data science towards green computing to overcome the environmental issues which have resulted in establishing data centers. The centers are gaining impute importance across the global especially in countries like America which is technology0oriented and is serving to maintain longlasting working environments..

Keywords

Data warehouse, Big Data, Computing, Data Transformation, Meta data, Apple, Green Computing.

References

[1] Amir G, Murtaza H, (2015) “Beyond the hype: Big data concepts, methods, and analytics”.
[2] Chen, Edward T. (2012) "Implementation Issues of Enterprise data Warehousing and Business Intelligence
[3]Colocation America (2018) How data centers are going green. Retrieved from: https://www.colocationamerica.com/blog/how-data-centerssave- energy
[4] Jia R., Xu S., Peng C. (2013) Research on Real Time Data Warehouse Architecture. Communications in Computer and Information Science, vol 392. Springer, Berlin, Heidelberg. 2013. Elsevier.
[5] Khan A, Ehsan N, Mirza E, & Sarwar SZ (2013). “Integration between Customer Relationship Management (CRM) and Data Warehousing”. Procedia Technology, 1, 239-249.
[6] Nathan M, & James W, (2015) Big Data: Principles and best practices of scalable realtime data systems.
[7]Philips Woods (2017) Why Big Data demands new technology. Retrieved from: https://www.itproportal.com/features/why-big-data-demandsnew- technology
[8] Robert Laberge (2011) The data warehouse mentor: Practical data warehouse and business intelligence insights.