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DOI: 10.14569/IJACSA.2020.0110854
PDF

Lake Data Warehouse Architecture for Big Data Solutions

Author 1: Emad Saddad
Author 2: Ali El-Bastawissy
Author 3: Hoda M. O. Mokhtar
Author 4: Maryam Hazman

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 11 Issue 8, 2020.

  • Abstract and Keywords
  • How to Cite this Article
  • {} BibTeX Source

Abstract: Traditional Data Warehouse is a multidimensional repository. It is nonvolatile, ‎subject-oriented, integrated, time-variant, and non-‎operational data. It is gathered from multiple ‎heterogeneous data ‎sources. We need to adapt traditional Data Warehouse architecture to deal with the new ‎challenges imposed by the abundance of data and the current big data characteristics, containing ‎volume, value, variety, validity, volatility, visualization, variability, and venue. The new ‎architecture also needs to handle existing drawbacks, including availability, scalability, and ‎consequently query performance. This paper introduces a novel Data Warehouse architecture, named Lake ‎Data Warehouse Architecture, to provide the traditional Data Warehouse with the capabilities to ‎overcome the challenges. ‎Lake Data Warehouse Architecture depends on merging the traditional Data Warehouse architecture ‎with big data technologies, like the Hadoop framework and Apache Spark. It provides a hybrid ‎solution in a complementary way. The main advantage of the proposed architecture is that it ‎integrates the current features in ‎traditional Data Warehouses and big data features acquired ‎through integrating the ‎traditional Data Warehouse with Hadoop and Spark ecosystems. Furthermore, it is ‎tailored to handle a tremendous ‎volume of data while maintaining availability, reliability, and ‎scalability.‎

Keywords: Traditional data warehouse; big data; semi-structured data; unstructured data; novel data warehouses architecture; Hadoop; spark

Emad Saddad, Ali El-Bastawissy, Hoda M. O. Mokhtar and Maryam Hazman, “Lake Data Warehouse Architecture for Big Data Solutions” International Journal of Advanced Computer Science and Applications(IJACSA), 11(8), 2020. http://dx.doi.org/10.14569/IJACSA.2020.0110854

@article{Saddad2020,
title = {Lake Data Warehouse Architecture for Big Data Solutions},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2020.0110854},
url = {http://dx.doi.org/10.14569/IJACSA.2020.0110854},
year = {2020},
publisher = {The Science and Information Organization},
volume = {11},
number = {8},
author = {Emad Saddad and Ali El-Bastawissy and Hoda M. O. Mokhtar and Maryam Hazman}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

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