Journal Home > Volume 2 , Issue 1

In recent years, huge amounts of structured, unstructured, and semi-structured data have been generated by various institutions around the world and, collectively, this heterogeneous data is referred to as big data. The health industry sector has been confronted by the need to manage the big data being produced by various sources, which are well known for producing high volumes of heterogeneous data. Various big-data analytics tools and techniques have been developed for handling these massive amounts of data, in the healthcare sector. In this paper, we discuss the impact of big data in healthcare, and various tools available in the Hadoop ecosystem for handling it. We also explore the conceptual architecture of big data analytics for healthcare which involves the data gathering history of different branches, the genome database, electronic health records, text/imagery, and clinical decisions support system.


menu
Abstract
Full text
Outline
About this article

Big Data Analytics for Healthcare Industry: Impact, Applications, and Tools

Show Author's information Sunil Kumar( )Maninder Singh
Directorate of Livestock Farms, Guru Angad Dev Veterinary and Animal Sciences University, Ludhiana, India.
Department of Computer Science, Punjabi University, Patiala, India.

Abstract

In recent years, huge amounts of structured, unstructured, and semi-structured data have been generated by various institutions around the world and, collectively, this heterogeneous data is referred to as big data. The health industry sector has been confronted by the need to manage the big data being produced by various sources, which are well known for producing high volumes of heterogeneous data. Various big-data analytics tools and techniques have been developed for handling these massive amounts of data, in the healthcare sector. In this paper, we discuss the impact of big data in healthcare, and various tools available in the Hadoop ecosystem for handling it. We also explore the conceptual architecture of big data analytics for healthcare which involves the data gathering history of different branches, the genome database, electronic health records, text/imagery, and clinical decisions support system.

Keywords: big data, MapReduce, Hadoop, healthcare

References(43)

[1]
A. Gandomi and M. Haider, Beyond the hype: Big data concepts, methods and analytics, International Journal of Information Management, vol. 35, no. 2, pp. 137-144, 2015.
[2]
A. O’Driscoll, J. Daugelaite, and R. D. Sleator, "Big Data", Hadoop and cloud computing in genomics, Journal of Biomedical Informatics, vol. 46, no. 5, pp. 774-781, 2013.
[3]
C. L. P. Chen and C. Y. Zhang, Data-intensive applications, challenges, techniques and technologies: A survey on big data, Information Sciences, vol. 275, pp. 314-347, 2014.
[4]
M. Herland, T. M. Khoshgoftaar, and R. Wald, A review of data mining using big data in health informatics, Journal of Big Data, vol. 1, no. 1, p. 2, 2014.
[5]
D. H. Shin and M. J. Choi, Ecological views of big data: Perspective and issues, Telematics and Informatics, vol. 32, no. 2, pp. 311-320, 2015.
[6]
B. Saraladevi, N. Pazhaniraja, P. V. Paul, M. S. Basha, and P. Dhavachelvan, Big data and Hadoop-A study in security perspective, Procedia Computer Science, vol. 50, pp. 596-601, 2015.
[7]
X. Wu, X. Zhu, G. Q. Wu, and W. Ding, Data mining with big data, IEEE transactions on Knowledge and Data Engineering, vol. 26, no. 1, pp. 97-107, 2014.
[8]
S. Sharma and V. Mangat, Technology and trends to handle big data: Survey, in Proc. 5th International Conference on Advanced Computing & Communication Technologies, 2015, pp. 266-271.
DOI
[9]
R. Mehmood and G. Graham, Big data logistics: A health-care transport capacity sharing model, Procedia Computer Science, vol. 64, pp. 1107-1114, 2015.
[10]
D. P. Augustine, Leveraging big data analytics and Hadoop in developing India healthcare services, International Journal of Computer Applications, vol. 89, no. 16, pp. 44-50, 2014.
[11]
J. A. Patel and P. Sharma, Big data for better health planning, in Proc. International Conference on Advances in Engineering and Technology Research, 2014, pp. 1-5.
DOI
[12]
A. E. Youssef, A framework for secure healthcare systems based on big data analytics in mobile cloud computing environments, International Journal of Ambient Systems and Applications, vol. 2, no. 2, pp. 1-11, 2014.
[13]
MAPR, Healthcare and life science use cases, https://mapr.com/solutions/industry/healthcare-and-lifescience-use-cases/, 2018.
[14]
W. Raghupathi and V. Raghupathi, Big data analytics in healthcare: Promise and potential, Health Information Science and Systems, vol. 2, no. 1, p. 3, 2014.
[15]
J. Sun and C. K. Reddy, Big data analytics for healthcare, in Proc. 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2013, pp. 1525-1525.
DOI
[16]
C. Mike, W. Hoover, T. Strome, and S. Kanwal. Transforming health care through big data strategies for leveraging big data in the health care industry, http://ihealthtran.com/iHT2 BigData 2013.pdf, 2013.
[17]
J. Anuradha, A brief introduction on big data 5Vs characteristics and Hadoop technology, Procedia Computer Science, vol. 48, pp. 319-324, 2015.
[18]
M. Viceconti, P. J. Hunter, and R. D. Hose, Big data, big knowledge: Big data for personalized healthcare, IEEE Journal of Biomedical and Health Informatics, vol. 19, no. 4, pp. 1209-1215, 2015.
[19]
Y. Sun, H. Song, A. J. Jara, and R. Bie, Internet of things and big data analytics for smart and connected communities, IEEE Access, vol. 4, pp. 766-773, 2016.
[20]
A. Jain and V. Bhatnagar, Crime data analysis using Pig with Hadoop, Procedia Computer Science, vol. 78, pp. 571-578, 2016.
[21]
T. Jach, E. Magiera, and W. Froelich, Application of Hadoop to store and process big data gathered from an urban water distribution system, Procedia Engineering, vol. 119, pp. 1375-1380, 2015.
[22]
C. Uzunkaya, T. Ensari, and Y. Kavurucu, Hadoop ecosystem and its analysis on tweets, Procedia-Social and Behavioral Sciences, vol. 195, pp. 1890-1897, 2015.
[23]
S. G. Manikandan and S. Ravi, Big data analysis using Apache Hadoop, in Proc. International Conference on IT Convergence and Security, 2014, pp. 1-4.
DOI
[24]
V. Ubarhande, A. M. Popescu, and H. Gonzalez-Velez, Novel data-distribution technique for Hadoop in heterogeneous cloud environment, in Proc. 9th International Conference on Complex, Intelligent, and Software Intensive Systems, 2015, pp. 217-224.
DOI
[25]
S. Maitrey and C. K. Jha, Handling big data efficiently by using map reduce technique, in Proc. International Conference on Computational Intelligence & Communication Technology, 2015, pp. 703-708.
DOI
[26]
J. Dean and S. Ghemawat, MapReduce: Simplified data processing on large clusters, Communications of the ACM, vol. 51, no. 1, pp. 107-113, 2008.
[27]
[28]
R. Misra, B. Panda, and M. Tiwary, Big data and ICT applications: A study, in Proc. 2nd International Conference on Information and Communication Technology for Competitive Strategies, 2016, p. 41.
DOI
[29]
A. G. Picciano, The evolution of big data and learning analytics in american higher education, Journal of Asynchronous Learning Networks, vol. 16, no. 3, pp. 9-20, 2012.
[30]
Apache Hadoop, http://hadoop.apache.org/, 2018.
[31]
A. Katal, M. Wazid, R. H. Goudar, and T. Noel, Big data: Issues, challenges, tools and good practices, in Proc. 6th International Conference on Contemporary Computing, 2013, pp. 404-409.
DOI
[32]
Apache Hive, https://hive.apache.org/, 2018.
DOI
[33]
K. K. Y. Lee, W. C. Tang, and K. S. Choi, Alternatives to relational database: Comparison of NoSQL and XML approaches for clinical data storage, Computer Methods and Programs in Biomedicine, vol. 110, no. 1, pp. 99-109, 2013.
[34]
Apache Pig, https://pig.apache.org/, 2018.
[35]
E. Dede, B. Sendir, P. Kuzlu, J. Weachock, M. Govindaraju, and L. Ramakrishnan, Processing Cassandra datasets with Hadoop-streaming based approaches, IEEE Transactions on Services Computing, vol. 9, no. 1, pp. 46-58, 2016.
[36]
Apache HBase, http://hbase.apache.org/, 2018.
[37]
Apache Oozie, https://oozie.apache.org/, 2018.
[38]
Apache Avro, https://avro.apache.org/, 2018.
[39]
Apache Zookeeper, https://zookeeper.apache.org/, 2018.
[40]
[41]
Apache Yarn, https://yarn.apache.org/, 2018.
[42]
Apache Sqoop, https://sqoop.apache.org/, 2018.
[43]
Apache Flume, https://flume.apache.org/, 2018.
Publication history
Copyright
Rights and permissions

Publication history

Received: 16 May 2018
Accepted: 02 August 2018
Published: 15 October 2018
Issue date: March 2019

Copyright

© The author(s) 2019

Rights and permissions

Return