scholarly journals Big Data Analytics With Reference To Wide Variety of Domains

2019 ◽  
Vol 8 (10) ◽  
pp. 1100-1104
Keyword(s):  
Health Care ◽  
Social Networks ◽  
Big Data ◽  
Data Analytics ◽  
High Speed ◽  
Big Data Analytics ◽  
Huge Amount ◽  
Government Sector ◽  
Big Data Technologies ◽  
Survey Results

In the current day scenario, a huge amount of data is been generated from various heterogeneous sources like social networks, business apps, government sector, marketing, health care system, sensors, machine log data which is created at such a high speed and other sources. Big Data is chosen as one among the upcoming area of research by several industries. In this paper, the author presents wide collection of literature that has been reviewed and analyzed. This paper emphasizes on Big Data Technologies, Application & Challenges, a comparative study on architectures, methodologies, tools, and survey results proposed by various researchers are presented

Strategic issues of big data analytics applications for managing health-care sector: a systematic literature review and future research agenda

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Rajesh Kumar Singh ◽  
Saurabh Agrawal ◽  
Abhishek Sahu ◽  
Yigit Kazancoglu
Keyword(s):  
Health Care ◽  
Big Data ◽  
Literature Review ◽  
Systematic Literature Review ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Health Care Sector ◽  
Future Research ◽  
Research Gaps ◽  
Content Type

PurposeThe proposed article is aimed at exploring the opportunities, challenges and possible outcomes of incorporating big data analytics (BDA) into health-care sector. The purpose of this study is to find the research gaps in the literature and to investigate the scope of incorporating new strategies in the health-care sector for increasing the efficiency of the system.Design/methodology/approachFora state-of-the-art literature review, a systematic literature review has been carried out to find out research gaps in the field of healthcare using big data (BD) applications. A detailed research methodology including material collection, descriptive analysis and categorization is utilized to carry out the literature review.FindingsBD analysis is rapidly being adopted in health-care sector for utilizing precious information available in terms of BD. However, it puts forth certain challenges that need to be focused upon. The article identifies and explains the challenges thoroughly.Research limitations/implicationsThe proposed study will provide useful guidance to the health-care sector professionals for managing health-care system. It will help academicians and physicians for evaluating, improving and benchmarking the health-care strategies through BDA in the health-care sector. One of the limitations of the study is that it is based on literature review and more in-depth studies may be carried out for the generalization of results.Originality/valueThere are certain effective tools available in the market today that are currently being used by both small and large businesses and corporations. One of them is BD, which may be very useful for health-care sector. A comprehensive literature review is carried out for research papers published between 1974 and 2021.

scholarly journals BIG DATA BUSINESS ANALYTICS AS A STRATEGIC ASSET FOR HEALTH CARE INDUSTRY

2019 ◽  
Vol 01 (02) ◽  
pp. 12-20 ◽  
Author(s):  
Smys S ◽  
Vijesh joe C
Keyword(s):  
Health Care ◽  
Big Data ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Health Care Industry ◽  
Customer Relationship ◽  
Business Strategies ◽  
Business Analytics ◽  
Care Industry ◽  
Strategic Assets

The big data includes the enormous flow of data from variety of applications that does not fit into the traditional data base. They deal with the storing, managing and manipulating of the data acquired from various sources at an alarming rate to gather valuable insights from it. The big data analytics is used provide with the new and better ideas that pave way to the improvising of the business strategies with its broader, deeper insights and frictionless actions that leads to an accurate and reliable systems. The paper proposes the big data analytics for the improving the strategic assets in the health care industry by providing with the better services for the patients, gaining the satisfaction of the patients and enhancing the customer relationship.

Insight Into Big Data Analytics

2018 ◽  
pp. 67-79
Author(s):  
Mohd Vasim Ahamad ◽  
Misbahul Haque ◽  
Mohd Imran
Keyword(s):  
Big Data ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Healthcare Services ◽  
Huge Amount ◽  
Business Decision ◽  
Digital Era ◽  
Data Formats ◽  
Recent Trends ◽  
Analytical Approaches

In the present digital era, more data are generated and collected than ever before. But, this huge amount of data is of no use until it is converted into some useful information. This huge amount of data, coming from a number of sources in various data formats and having more complexity, is called big data. To convert the big data into meaningful information, the authors use different analytical approaches. Information extracted, after applying big data analytics methods over big data, can be used in business decision making, fraud detection, healthcare services, education sector, machine learning, extreme personalization, etc. This chapter presents the basics of big data and big data analytics. Big data analysts face many challenges in storing, managing, and analyzing big data. This chapter provides details of challenges in all mentioned dimensions. Furthermore, recent trends of big data analytics and future directions for big data researchers are also described.

Semantic Technologies and Big Data Analytics for Cyber Defence

Web Services ◽  
2019 ◽  
pp. 1430-1443
Author(s):  
Louise Leenen ◽  
Thomas Meyer
Keyword(s):  
Decision Making ◽  
Big Data ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Future Research ◽  
Data Sets ◽  
Semantic Technologies ◽  
Data Types ◽  
Intelligent Decision Making ◽  
Big Data Technologies

The Governments, military forces and other organisations responsible for cybersecurity deal with vast amounts of data that has to be understood in order to lead to intelligent decision making. Due to the vast amounts of information pertinent to cybersecurity, automation is required for processing and decision making, specifically to present advance warning of possible threats. The ability to detect patterns in vast data sets, and being able to understanding the significance of detected patterns are essential in the cyber defence domain. Big data technologies supported by semantic technologies can improve cybersecurity, and thus cyber defence by providing support for the processing and understanding of the huge amounts of information in the cyber environment. The term big data analytics refers to advanced analytic techniques such as machine learning, predictive analysis, and other intelligent processing techniques applied to large data sets that contain different data types. The purpose is to detect patterns, correlations, trends and other useful information. Semantic technologies is a knowledge representation paradigm where the meaning of data is encoded separately from the data itself. The use of semantic technologies such as logic-based systems to support decision making is becoming increasingly popular. However, most automated systems are currently based on syntactic rules. These rules are generally not sophisticated enough to deal with the complexity of decisions required to be made. The incorporation of semantic information allows for increased understanding and sophistication in cyber defence systems. This paper argues that both big data analytics and semantic technologies are necessary to provide counter measures against cyber threats. An overview of the use of semantic technologies and big data technologies in cyber defence is provided, and important areas for future research in the combined domains are discussed.

Big Data Analytics in Aquaculture Using Hive and Hadoop Platform

2018 ◽  
pp. 29-35
Author(s):  
P. Venkateswara Rao ◽  
A. Ramamohan Reddy ◽  
V. Sucharita
Keyword(s):  
Big Data ◽  
Data Management ◽  
Single Machine ◽  
Data Analytics ◽  
Historical Data ◽  
Big Data Analytics ◽  
Huge Amount ◽  
Hadoop Platform ◽  
Different Sources

In the field of Aquaculture with the help of digital advancements huge amount of data is constantly produced for which the data of the aquaculture has entered in the big data world. The requirement for data management and analytics model is increased as the development progresses. Therefore, all the data cannot be stored on single machine. There is need for solution that stores and analyzes huge amounts of data which is nothing but Big Data. In this chapter a framework is developed that provides a solution for shrimp disease by using historical data based on Hive and Hadoop. The data regarding shrimps is acquired from different sources like aquaculture websites, various reports of laboratory etc. The noise is removed after the collection of data from various sources. Data is to be uploaded on HDFS after normalization is done and is to be put in a file that supports Hive. Finally classified data will be located in particular place. Based on the features extracted from aquaculture data, HiveQL can be used to analyze shrimp diseases symptoms.

Real Time Analysis Based on Intelligent Applications of Big Data and IoT in Smart Health Care Systems

2020 ◽  
pp. 1839-1857
Author(s):  
Mamata Rath
Keyword(s):  
Health Care ◽  
Big Data ◽  
Data Analytics ◽  
Treatment Plan ◽  
Big Data Analytics ◽  
Data Sets ◽  
Care Services ◽  
Real Time Analysis ◽  
Health Care Applications ◽  
Care Systems

Currently, there is an expanding interest for additional medical data from patients about their healthcare choices and related decisions, and they further need investment in their basic health issues. Big data provides patients presumptuous data to help them settle on the best choice and align with their medicinal treatment plan. One of the very advanced concepts related to the synthesis of big data sets to reveal the hidden pattern in them is big data analytics. It involves demanding techniques to mine and extract relevant data that includes the actions of piercing a database, effectively mine the data, query and inspect the data and is committed to enhance the technical execution of various task segments. The capacity to synthesize a lot of data can enable an association to manage data that can influence the business. In this way, the primary goal of big data analytics is to help business relationships to have enhanced comprehension of data, and subsequently, settle on proficient and very much educated decisions. Big data analytics empowers data diggers and researchers to examine an extensive volume of data that may not be outfit utilizing customary apparatuses. Big data analytics require advances and statistical instruments that can change a lot of organized, unstructured, and semi-organized data into more reasonable data and metadata designed for explanatory procedures. There is tremendous positive potential concerning the application of big data in human health care services and many related major applications are still in their developmental stages. The deployment of big data in health service demonstrates enhancing health care results and controlling the expenses of common people due to treatment, as proven by some developing use cases. Keeping in view such powerful processing capacity of big data analytics in various technical fields of modern civilization related to health care, the current research article presents a comprehensive study and investigation on big data analytics and its application in multiple sectors of society with significance in health care applications.

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