International Journal on Data Science and Technology

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Data Analysis: Types, Process, Methods, Techniques and Tools

Received: 11 December 2019    Accepted: 25 December 2019    Published: 06 January 2020
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Abstract

The process of evaluating data using analytical and logical reasoning to examine each component of the data provided. This form of analysis is just one of the many steps that must be completed when conducting a research experiment. Data from various sources is gathered, reviewed, and then analyzed to form some sort of finding or conclusion. There are a variety of specific data analysis method, some of which include data mining, text analytics, business intelligence, and data visualizations. Data analysis is defined as a process of cleaning, transforming, and modeling data to discover useful information for business decision-making. The purpose of Data Analysis is to extract useful information from data and taking the decision based upon the data analysis. whenever we take any decision in our day-to-day life is by thinking about what happened last time or what will happen by choosing that particular decision. This is nothing but analyzing our past or future and making decisions based on it. For that, we gather memories of our past or dreams of our future. So that is nothing but data analysis. Now same thing analyst does for business purposes, is called Data Analysis. This research article based on data analysis, it’s types, process, methods, techniques & tools.

DOI 10.11648/j.ijdst.20200601.12
Published in International Journal on Data Science and Technology (Volume 6, Issue 1, March 2020)
Page(s) 10-15
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

Data, Visualization, Data Analysis, Business, Statistics

References
[1] Sardar Mohkim Khan (26 January 2011). "DataMarket Expands Horizons: Adds 100 Million Time Series, 600 Million Facts".
[2] Tamara Munzner. "Process and Pitfalls in Writing Information Visualization Research Papers". www.cs.ubc.ca. Retrieved 9 April 2018.
[3] Pavlopoulos, Georgios A.; Iacucci, Ernesto; Iliopoulos, Ioannis; Bagos, Pantelis (2013). Interpreting the Omics 'era' Data. Multimedia Services in Intelligent Environments. Smart Innovation, Systems and Technologies.
[4] Benjamin B. Bederson and Ben Shneiderman (2003). The Craft of Information Visualization: Readings and Reflections, Morgan Kaufmann ISBN 1-55860-915-6.
[5] Manuela Aparicio and Carlos J. Costa (November 2014). "Data visualization". Communication Design Quarterly Review.
[6] "Data Visualization for Human Perception". The Interaction Design Foundation. Retrieved 2015-11-23.
[7] Lucić V, Förster F, Baumeister W (2005). "Structural studies by electron tomography: from cells to molecules". Annual Review of Biochemistry. 74: 833–65.
[8] Chang, J. Dean, S. Ghemawat, W. C. Hsieh, D. A. Wallach, M. Burrows, T. Chandra, A. Fikes, and R. E. Gruber. Bigtable: A Distributed Storage System for Structured Data. In OSDI, pages205–218, 2006.
[9] Rajeev Gupta, Himanshu Gupta, and Mukesh Mohania, "Cloud Computing and Big Data Analytics: What Is New from Database s Perspective?" S. Srinivasa and V. Bhatnagar (Eds.): BDA 2012, LNCS 7678, pp. Springer-Verlag Berlin Heidelberg 42–61, 2012.
[10] Curino, C., Jones, E. P. C., Popa, R. A., Malviya, N., Wu, E., Madden, S., Balakrishnan, H., Zeldovich, N.: Realtional Cloud: A Database-as-a-Service for the Cloud. In: Proceedings of Conference on Innovative Data Systems Research, CIDR-2011.
[11] Alberto Ferandez, Sara del R, Victoria opez, Abdullah Bawakid, Maria J. del Jesus, Jose M. Benitez, and Francisco Herrera. "Big Data with Cloud Computing: an insight on the computingenvironment, MapReduce, and programming frameworks". doi: 10.1002/widm.1134. WIREs Data Mining Knowl Discov, 4: 380–409, 2014.
[12] Lu, Huang, Ting-tin Hu, and Hai-shan Chen. "Research on Hadoop Cloud Computing Model and its Applications.". Hangzhou, China: 2012, pp. 59–63, 21-24 Oct. 2012.
[13] Wie, Jiang, Ravi V. T, and Agrawal G. "A Map-Reduce System with an Alternate API for Multi-core Environments.". Melbourne, VIC: 2010, pp. 84-93, 17-20 May. 2010.
[14] K, Chitharanjan, and Kala Karun A. "A review on hadoop - HDFS infrastructure exten-sions.". JeJu Island: 2013, pp. 132-137, 11-12 Apr. 2013.
[15] F. C. P, Muhtaroglu, Demir S, Obali M, and Girgin C. "Business model canvas perspective on big data applications." Big Data, 2013 IEEE International Conference, Silicon Valley, CA, Oct 6-9, p. 32–37, 2013.
[16] Castelino, C., Gandhi, D., Narula, H. G., & Chokshi, N. H. (2014). Integration of Big Data and Cloud Computing. International Journal of Engineering Trends and Technology (IJETT), 100-102.
Author Information
  • School of Intelligent Technology and Engineering, Chongqing University of Science and Technology, Chongqing, China

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  • APA Style

    Mohaiminul Islam. (2020). Data Analysis: Types, Process, Methods, Techniques and Tools. International Journal on Data Science and Technology, 6(1), 10-15. https://doi.org/10.11648/j.ijdst.20200601.12

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    ACS Style

    Mohaiminul Islam. Data Analysis: Types, Process, Methods, Techniques and Tools. Int. J. Data Sci. Technol. 2020, 6(1), 10-15. doi: 10.11648/j.ijdst.20200601.12

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    AMA Style

    Mohaiminul Islam. Data Analysis: Types, Process, Methods, Techniques and Tools. Int J Data Sci Technol. 2020;6(1):10-15. doi: 10.11648/j.ijdst.20200601.12

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  • @article{10.11648/j.ijdst.20200601.12,
      author = {Mohaiminul Islam},
      title = {Data Analysis: Types, Process, Methods, Techniques and Tools},
      journal = {International Journal on Data Science and Technology},
      volume = {6},
      number = {1},
      pages = {10-15},
      doi = {10.11648/j.ijdst.20200601.12},
      url = {https://doi.org/10.11648/j.ijdst.20200601.12},
      eprint = {https://download.sciencepg.com/pdf/10.11648.j.ijdst.20200601.12},
      abstract = {The process of evaluating data using analytical and logical reasoning to examine each component of the data provided. This form of analysis is just one of the many steps that must be completed when conducting a research experiment. Data from various sources is gathered, reviewed, and then analyzed to form some sort of finding or conclusion. There are a variety of specific data analysis method, some of which include data mining, text analytics, business intelligence, and data visualizations. Data analysis is defined as a process of cleaning, transforming, and modeling data to discover useful information for business decision-making. The purpose of Data Analysis is to extract useful information from data and taking the decision based upon the data analysis. whenever we take any decision in our day-to-day life is by thinking about what happened last time or what will happen by choosing that particular decision. This is nothing but analyzing our past or future and making decisions based on it. For that, we gather memories of our past or dreams of our future. So that is nothing but data analysis. Now same thing analyst does for business purposes, is called Data Analysis. This research article based on data analysis, it’s types, process, methods, techniques & tools.},
     year = {2020}
    }
    

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    AB  - The process of evaluating data using analytical and logical reasoning to examine each component of the data provided. This form of analysis is just one of the many steps that must be completed when conducting a research experiment. Data from various sources is gathered, reviewed, and then analyzed to form some sort of finding or conclusion. There are a variety of specific data analysis method, some of which include data mining, text analytics, business intelligence, and data visualizations. Data analysis is defined as a process of cleaning, transforming, and modeling data to discover useful information for business decision-making. The purpose of Data Analysis is to extract useful information from data and taking the decision based upon the data analysis. whenever we take any decision in our day-to-day life is by thinking about what happened last time or what will happen by choosing that particular decision. This is nothing but analyzing our past or future and making decisions based on it. For that, we gather memories of our past or dreams of our future. So that is nothing but data analysis. Now same thing analyst does for business purposes, is called Data Analysis. This research article based on data analysis, it’s types, process, methods, techniques & tools.
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