@article{MAKHILLJEAS2019142018524,
    title = {Big Data Harmonization-Data Loading and Data Storage},
    journal = {Journal of Engineering and Applied Sciences},
    volume = {14},
    number = {20},
    pages = {7731-7735},
    year = {2019},
    issn = {1816-949x},
    doi = {jeasci.2019.7731.7735},
    url = {https://makhillpublications.co/view-article.php?issn=1816-949x&doi=jeasci.2019.7731.7735},
    author = {Jitali,Priyanka and},
    keywords = {heterogeneous data,Hadoop,OLAP,Data warehouse,programming model,data storage process},
    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.}
    }