Journal of Engineering and Applied Sciences
ISSN: Online 1818-7803ISSN: Print 1816-949x
Abstract
With the wide and fast development of tools and technology in big data era, new challenges in development of OLAP and data harmonization become the essential. Data harmonization provide the common level of granularity from the heterogeneous data sources and with the variety of data formats. To manage big data, distributed environment and Hadoop framework are only the solution. Exponentially increasing data create scalability issue in any model, map reduce programming model resolves that problem. Using these technologies we present series of algorithms combined in our model OOH (Olap on Hadoop) to show the data loading and data storage process.
How to cite this article:
Jitali Patel, Priyanka Sharma and Jigna Patel. Big Data Harmonization-Data Loading and Data Storage.
DOI: https://doi.org/10.36478/jeasci.2019.7731.7735
URL: https://www.makhillpublications.co/view-article/1816-949x/jeasci.2019.7731.7735