The Interactive Visualization Gap in Initial Exploratory Data Science and Analysis

Authors

  • Md Shahid Ahmad, Ravi Kumar, Md. Talib Ahmad, Niraj Kumar

Keywords:

Big Data, Heterogeneous, Visualization, Distribute Data Value

Abstract

Complexity is one of the defining features of data scaling. When it comes to big data and data integration, heterogeneous data is a major factor. Both are necessary, but enormous amounts of data processing and storage make it hard to see and understand big databases. Data extraction in a way that the human brain can understand is a major challenge in this data-driven era of exponential data growth. This study summarizes and offers a description of heterogeneous distributed storage, data visualization, and the difficulties associated with it, drawing on a variety of approaches from prior studies. In addition, we compare the findings of the examined research works and talk about the major change happening in the field of virtual reality huge data visualization.

Downloads

Download data is not yet available.

References

Abdullah, P. Y., Zeebaree, S. R., Jacksi, K., & Zeabri, R. R. (2020). AN HRM SYSTEM FOR SMALL AND MEDIUM

ENTERPRISES (SME) S BASED ON CLOUD COMPUTING TECHNOLOGY. International Journal of Research- GRANTHAALAYAH, 8(8), 56–64.

Ali, S. M., Gupta, N., Nayak, G. K., & Lenka, R. K. (2016). Big data visualization: Tools and challenges. 656–660.

Alzakholi, O., Haji, L., Shukur, H., Zebari, R., Abas, S., & Sadeeq, M. (2020). Comparison Among Cloud Technologies and Cloud Performance. Journal of Applied Science and Technology Trends, 1(2), 40–47. https://doi.org/10.38094/jastt1219

Byron, L., & Wattenberg, M. (2008). Stacked graphs–geometry & aesthetics. IEEE Transactions on Visualization and Computer Graphics, 14(6), 1245–1252.

Caldarola, E. G., & Rinaldi, A. M. (2017). Big Data Visualization Tools: A Survey. Research Gate.

Caldarola, E. G., Sacco, M., & Terkaj, W. (2014). Big data: The current wave front of the tsunami. Applied Computer Science, 10(4), Article 4.

Carranza, A. G., Rossi, R. A., Rao, A., & Koh, E. (2020). Higher-order clustering in complex heterogeneous networks.

25–35.

Chawla, G., Bamal, S., & Khatana, R. (2018). Big Data Analytics for Data Visualization: Review of Techniques’.

International Journal of Computer Applications, 182(21), 37–40.

Chen, C. P., & Zhang, C.-Y. (2014). Data-intensive applications, challenges, techniques and technologies: A survey on Big Data. Information Sciences, 275, 314–347.

Dino, H., Abdulrazzaq, M. B., Zeebaree, S. R., Sallow, A. B., Zebari, R. R., Shukur, H. M., & Haji, L. M. (2020). Facial Expression Recognition based on Hybrid Feature Extraction Techniques with Different Classifiers. TEST Engineering & Management, 83, 22319–22329.

Dino, Hivi I., & Abdulrazzaq, M. B. (2020). A Comparison of Four Classification Algorithms for Facial Expression Recognition. Polytechnic Journal, 10(1), 74–80.

Dino, Hivi Ismat, & Abdulrazzaq, M. B. (2019). Facial Expression Classification Based on SVM, KNN and MLP Classifiers. 2019 International Conference on Advanced Science and Engineering (ICOASE), 70–75.

Dino, Hivi Ismat, Zeebaree, S. R., Ahmad, O. M., Shukur, H. M., Zebari, R. R., & Haji, L. M. (2020). Impact of Load Sharing on Performance of Distributed Systems Computations. International Journal of Multidisciplinary Research and Publications (IJMRAP), 3(1), 30–37.

Dino, Hivi Ismat, Zeebaree, S. R., Salih, A. A., Zebari, R. R., Ageed, Z. S., Shukur, H. M., Haji, L. M., & Hasan, S. S. (2020). Impact of Process Execution and Physical Memory-Spaces on OS Performance. Technology Reports of Kansai University, 62(5), 2391–2401.

Dragland, A. (2013). Big Data–for better or worse. SINTEF. No. 22 May 2013. Web. 27 Oct.

Fiaz, A. S., Asha, N., Sumathi, D., & Navaz, A. S. (2016). Data visualization: Enhancing big data more adaptable and valuable. International Journal of Applied Engineering Research, 11(4), 2801–2804.

Franks, B. (2012). Taming the big data tidal wave: Finding opportunities in huge data streams with advanced analytics (Vol. 49). John Wiley & Sons.

Haji, L. M., Zeebaree, S. R., Ahmed, O. M., Sallow, A. B., Jacksi, K., & Zeabri, R. R. (2020). Dynamic Resource Allocation for Distributed Systems and Cloud Computing. TEST Engineering & Management, 83(May/June 2020), 22417–22426.

Haji, L., Zebari, R. R., R. M. Zeebaree, S., Abduallah, W. M., M. Shukur, H., & Ahmed, O. (21, May). GPUs Impact on Parallel Shared Memory Systems Performance. International Journal of Psychosocial Rehabilitation, 24(08), 8030–8038. https://doi.org/10.37200/IJPR/V2418/PR280814

Iturbe, M., Garitano, I., Zurutuza, U., & Uribeetxeberria, R. (2017). Towards large-scale, heterogeneous anomaly detection systems in industrial networks: A survey of current trends. Security and Communication Networks, 2017.

Jader, O. H., Zeebaree, S. R., & Zebari, R. R. (2019). A State of Art Survey For Web Server Performance Measurement And Load Balancing Mechanisms. INTERNATIONAL JOURNAL OF SCIENTIFIC & TECHNOLOGY RESEARCH, 8(12), 535–543.

Johansson, J., Forsell, C., Lind, M., & Cooper, M. (2008). Perceiving patterns in parallel coordinates: Determining thresholds for identification of relationships. Information Visualization, 7(2), 152–162.

Kammer, D., Keck, M., Gründer, T., & Groh, R. (2018). Big data landscapes: Improving the visualization of machine learning-based clustering algorithms. 1–3.

Kaneko, S., Nakamura, T., Kamei, H., & Muraoka, H. (2016). A guideline for data placement in heterogeneous distributed storage systems. 942–945.

Keahey, T. A. (2013). Using visualization to understand big data. IBM Business Analytics Advanced Visualisation, 16.

Khalifa, I. A., Zeebaree, S. R., Ataş, M., & Khalifa, F. M. (2019). Image Steganalysis in Frequency Domain Using Co- Occurrence Matrix and Bpnn. Science Journal of University of Zakho, 7(1), 27–32.

Li, H., Li, H., Wen, Z., Mo, J., & Wu, J. (2017). Distributed heterogeneous storage based on data value. 264–271. Liang, C., & Zhou, L. (2019). Research on Distributed Storage of Big Data Based on HBase Remote Sensing Image. 1,

2628–2632.

Liu, Q., Guo, X., Fan, H., & Zhu, H. (2017). A novel data visualization approach and scheme for supporting heterogeneous data. 1259–1263.

Loorak, M., Perin, C., Collins, C., & Carpendale, S. (2017). Exploring the Possibilities of Embedding Heterogeneous Data Attributes in Familiar Visualizations. IEEE Transactions on Visualization and Computer Graphics, 23(1), 581–590.

Mahfoud, E., Wegba, K., Li, Y., Han, H., & Lu, A. (2018). Immersive visualization for abnormal detection in heterogeneous data for on-site decision making. Proceedings of the 51st Hawaii International Conference on System Sciences.

Mahmood, M. R., Abdulrazzaq, M. B., Zeebaree, S. R., Ibrahim, A. K., Zebari, R. R., & Dino, H. I. (2021). Classification techniques’ performance evaluation for facial expression recognition. Indonesian Journal of Electrical Engineering and Computer Science, 21(2), 176–1184.

Malik, K. R., Ahmad, T., Farhan, M., Aslam, M., Jabbar, S., Khalid, S., & Kim, M. (2016). Big-data: Transformation from heterogeneous data to semantically-enriched simplified data. Multimedia Tools and Applications, 75(20), 12727–12747.

Manyika, J., Chui, M., Brown, B., Bughin, J., Dobbs, R., Roxburgh, C., & Hung Byers, A. (2011). Big data: The next frontier for innovation, competition, and productivity. McKinsey Global Institute.

Mehmood, H., Gilman, E., Cortes, M., Kostakos, P., Byrne, A., Valta, K., Tekes, S., & Riekki, J. (2019). Implementing big data lake for heterogeneous data sources. 37–44.

Mohammad, O. F., Rahim, M. S. M., Zeebaree, S. R. M., & Ahmed, F. Y. (2017). A survey and analysis of the image encryption methods. International Journal of Applied Engineering Research, 12(23), 13265–13280.

Mustafa, O. M., Haji, D., Ahmed, O. M., & Haji, L. M. (2020). Big Data: Management, Technologies, Visualization, Techniques, and Privacy. Technology Reports of Kansai University, 62(05).

Obaid, K. B., Zeebaree, S. R., & Ahmed, O. M. (2020). Deep Learning Models Based on Image Classification: A Review. International Journal of Science and Business, 4(11), 75–81.

Olshannikova, E., Ometov, A., Koucheryavy, Y., & Olsson, T. (2015). Visualizing Big Data with augmented and virtual reality: Challenges and research agenda. Journal of Big Data, 2(1), 22.

Osanaiye, B. S., Ahmad, A. R., Mostafa, S. A., Mohammed, M. A., Mahdin, H., Subhi, R., Zeebaree, D. A. I., & Obaid, O.

(2019). Network Data Analyser and Support Vector Machine for Network Intrusion Detection of Attack Type. REVISTA AUS, 26(1), 91–104.

Saeed, R. H., Dino, H. I., Haji, L. M., Hamed, D. M., Shukur, H. M., & Jader, O. H. (2020). Impact of IoT Frameworks on Healthcare and Medical Systems Performance. International Journal of Science and Business, 5(1), 115–126.

Sallow, A. B., Zeebaree, S. R., Zebari, R. R., Mahmood, M. R., Abdulrazzaq, M. B., & Sadeeq, M. A. (2020). Vaccine Tracker/SMS Reminder System: Design and Implementation. International Journal of Multidisciplinary Research and Publications, 3(2), 57-63

Shukur, H., Zeebaree, S., Zebari, R., Ahmed, O., Haji, L., & Abdulqader, D. (2020). Cache Coherence Protocols in Distributed Systems. Journal of Applied Science and Technology Trends, 1(3), 92–97.

Shukur, H., Zeebaree, S., Zebari, R., Zeebaree, D., Ahmed, O., & Salih, A. (2020). Cloud Computing Virtualization of Resources Allocation for Distributed Systems. Journal of Applied Science and Technology Trends, 1(3), 98–105.

Tedesco, J., Dudko, R., Sharma, A., Farivar, R., & Campbell, R. (2013). Theius: A streaming visualization suite for hadoop clusters. 177–182.

Tennekes, M., & de Jonge, E. (2011). Top-down Data Analysis with Treemaps. 236–241.

Wang, L. (2017). Heterogeneous data and big data analytics. Automatic Control and Information Sciences, 3(1), 8– 15.

Weinberg, B. D., Davis, L., & Berger, P. D. (2013). Perspectives on big data. Journal of Marketing Analytics, 1(4), 187–201.

Woolsey, N., Chen, R.-R., & Ji, M. (2020). Coded Elastic Computing on Machines with Heterogeneous Storage and Computation Speed. ArXiv Preprint ArXiv:2008.05141.

Yu, L., & Yu, H. (2016). A study of scientific visualization on heterogeneous processors using Legion. 107–108. Zebari, D., Haron, H., & Zeebaree, S. R. (2017). Security Issues in DNA Based on Data Hiding: A Review.

International Journal of Applied Engineering Research ISSN 0973-4562, 12(24), 15363–15377.

Zebari, R., Abdulazeez, A., Zeebaree, D., Zebari, D., & Saeed, J. (2020). A Comprehensive Review of Dimensionality Reduction Techniques for Feature Selection and Feature Extraction. Journal of Applied Science and Technology Trends, 1(2), 56–70. https://doi.org/10.38094/jastt1224

Zebari, R. R., Zeebaree, S. R., & Jacksi, K. (2018). Impact Analysis of HTTP and SYN Flood DDoS Attacks on Apache

2 and IIS 10.0 Web Servers. 2018 International Conference on Advanced Science and Engineering (ICOASE), 156–161.

Zebari, R., Zeebaree, S., Jacksi, K., & Shukur, H. (2019). E-Business Requirements for Flexibility and Implementation Enterprise System: A Review. International Journal of Scientific & Technology Research, 8, 655–660.

Zeebaree, D. Q., Haron, H., Abdulazeez, A. M., & Zeebaree, S. R. (2017). Combination of K-means clustering with Genetic Algorithm: A review. International Journal of Applied Engineering Research, 12(24), 14238– 14245.

Zeebaree, S. R. (2020). DES encryption and decryption algorithm implementation based on FPGA. Indonesian Journal of Electrical Engineering and Computer Science, 18(2), 774–781.

Zeebaree, S. R., Jacksi, K., & Zebari, R. R. (2020). Impact analysis of SYN flood DDoS attack on HAProxy and NLB cluster-based web servers. Indonesian Journal of Electrical Engineering and Computer Science, 19(1), 510–517.

Zeebaree, S. R., Sallow, A. B., Hussan, B. K., & Ali, S. M. (2019). Design and Simulation of High-Speed Parallel/Sequential Simplified DES Code Breaking Based on FPGA. 2019 International Conference on Advanced Science and Engineering (ICOASE), 76–81.

Zeebaree, S. R., Shukur, H. M., & Hussan, B. K. (2019). Human resource management systems for enterprise organizations: A review. Periodicals of Engineering and Natural Sciences, 7(2), 660–669.

Zeebaree, S. R., Zebari, R. R., & Jacksi, K. (2020). Performance analysis of IIS10.0 and Apache2 Cluster-based Web Servers under SYN DDoS Attack. TEST Engineering & Management, 83(March-April 2020), 5854–5863.

Zeebaree, S. R., Zebari, R. R., Jacksi, K., & Hasan, D. A. (2019). Security Approaches For Integrated Enterprise Systems Performance: A Review. INTERNATIONAL JOURNAL OF SCIENTIFIC & TECHNOLOGY RESEARCH, 8(12).

Zeebaree, Subhi R. M., Haji, L. M., Rashid, I., Zebari, R. R., Ahmed, O. M., Jacksi, K., & Shukur, H. M. (2020). Multicomputer Multicore System Influence on Maximum Multi-Processes Execution Time. TEST Engineering & Management, 83(May/June), 14921–14931.

Zeebaree, Subhi R M, M. Shukur, H., M. Haji, L., Zebari, R. R., Jacksi, K., & M.Abas, S. (2020). Characteristics and Analysis of Hadoop Distributed Systems. Technology Reports of Kansai University, 62(4), 1555–1564.

Zeebaree, SUBHI R.M., Salim, B. wasfi, R. Zebari, R., Shukur, H. M., Abdulraheem, A. S., Abdulla, A. I., & Mohammed, S. M. (2020). Enterprise Resource Planning Systems and Challenges. Technology Reports of Kansai University, 62(4), 1885–1894.

Zhi, C. (2017). Research of Distributed Data Optimization Storage Model in the Cloud Computing Environment.

193–198.

Zhou, J., Chen, Y., Xie, W., Dai, D., He, S., & Wang, W. (2019). PRS: A Pattern-Directed Replication Scheme for Heterogeneous Object-Based Storage. IEEE Transactions on Computers, 69(4), 591–605.

Zhou, J., Xie, W., Gu, Q., & Chen, Y. (2016). Hierarchical consistent hashing for heterogeneous object-based storage.1597–1604.

Zhu, Y., Juniarto, S., Shi, H., & Wang, J. (2015). VH-DSI: speeding up data visualization via a heterogeneous distributed storage infrastructure. 658–665

Downloads

Published

26.03.2024

How to Cite

Ravi Kumar, Md. Talib Ahmad, Niraj Kumar, M. S. A. . (2024). The Interactive Visualization Gap in Initial Exploratory Data Science and Analysis. International Journal of Intelligent Systems and Applications in Engineering, 12(21s), 337–346. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/5428

Issue

Section

Research Article