Big Data Science and EXASOL as Big Data Analytics tool
Ajit Singh1, Sultan Ahmad2, Mohammad Imdadul Haque3
1Ajit Singh, Associate Professor, Department of Computer Science, Patna Women’s College, Patna University, Patna (Bihar), India.
2Sultan Ahmad, Department of Computer Science, prestigious Aligarh Muslim University, India.
3Mohammad Imdadul Haque, Associate Professor, Department of Computer Science, Prince Sattam Bin Abdulaziz University, Saudi Arabia.
Manuscript received on 08 August 2019 | Revised Manuscript received on 14 August 2019 | Manuscript Published on 26 August 2019 | PP: 933-937 | Volume-8 Issue-9S August 2019 | Retrieval Number: I11510789S19/19©BEIESP | DOI: 10.35940/ijitee.I1151.0789S19
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open-access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Big data and Data science are the two top trends of recent years. Both can be combined together as big data science. This leads to the demand for new system architectures which facilitates the development of processes which can handle huge data volumes without deterring the agility, flexibility and the interactive feel which suits the exploratory approach of a data scientist. Businesses today have found ways of using data as the principal factor for value generation. These data-driven businesses apply a variety of data tools as data analysis is one of the chief elements in this process. In order to raise data science to the new computational level that is required to meet the challenges of big data and interactive advanced analytics, EXASOL has introduced a new technological approach. This tool enables us more effective and easy data analysis.
Keywords: Big Data Science, EXASOL, Big Data, Data Science.
Scope of the Article: Big Data Analytics