Application of Big Data Tools for Unstructured Data Analysis to Improve ESP Operation Efficiency

2017 ◽  
Author(s):  
N. P. Sarapulov ◽  
R. A. Khabibullin
Keyword(s):  
Big Data ◽  
Data Analysis ◽  
Unstructured Data ◽  
Operation Efficiency

Survelliance of Type I and II Diabetic Subjects on Physical Characteristics

2021 ◽  
pp. 308-344
Author(s):  
Rohit Rastogi ◽  
Devendra Kumar Chaturvedi ◽  
Parul Singhal
Keyword(s):  
Big Data ◽  
Data Analysis ◽  
Electronic Health Records ◽  
Analysis Data ◽  
Healthcare Systems ◽  
Clinical Analysis ◽  
Big Data Analysis ◽  
Diagnostic Information ◽  
Unstructured Data ◽  
Type I

The Delhi and NCR healthcare systems are rapidly registering electronic health records and diagnostic information available electronically. Furthermore, clinical analysis is rapidly advancing, and large quantities of information are examined and new insights are part of the analysis of this technology experienced as big data. It provides tools for storing, managing, studying, and assimilating large amounts of robust, structured, and unstructured data generated by existing medical organizations. Recently, data analysis data have been used to help provide care. The present study aimed to analyse diabetes with the latest IoT and big data analysis techniques and its correlation with stress (TTH) on human health. The authors have tried to include age, gender, and insulin factor and its correlation with diabetes. Overall, in conclusion, TTH cases increasing with age in case of males and not following the pattern of diabetes variation with age, while in the case of females, TTH pattern variation is the same as diabetes (i.e., increasing trend up to age of 60 then decreasing).

Security Issues and Challenges Related to Big Data

2018 ◽  
pp. 86-101
Author(s):  
Jaimin N. Undavia ◽  
Atul Patel ◽  
Sheenal Patel
Keyword(s):  
Big Data ◽  
Data Analysis ◽  
Database Systems ◽  
Heterogeneous Data ◽  
Unstructured Data ◽  
Huge Amount ◽  
Current Time ◽  
Security Issues ◽  
Future Prediction ◽  
Data Term

Availability of huge amount of data has opened up a new area and challenge to analyze these data. Analysis of these data become essential for each organization and these analyses may yield some useful information for their future prospectus. To store, manage and analyze such huge amount of data traditional database systems are not adequate and not capable also, so new data term is introduced – “Big Data”. This term refers to huge amount of data which are used for analytical purpose and future prediction or forecasting. Big Data may consist of combination of structured, semi structured or unstructured data and managing such data is a big challenge in current time. Such heterogeneous data is required to maintained in very secured and specific way. In this chapter, we have tried to identify such challenges and issues and also tried to resolve it with specific tools.

Big Data Analysis

2021 ◽  
pp. 208-233
Author(s):  
Arpit Kumar Sharma ◽  
Arvind Dhaka ◽  
Amita Nandal ◽  
Kumar Swastik ◽  
Sunita Kumari
Keyword(s):  
Cloud Computing ◽  
Big Data ◽  
Data Analysis ◽  
Knowledge Extraction ◽  
Big Data Analysis ◽  
Unstructured Data ◽  
Data Sets ◽  
Data Handling ◽  
Software And Hardware

The meaning of the term “big data” can be inferred by its name itself (i.e., the collection of large structured or unstructured data sets). In addition to their huge quantity, these data sets are so complex that they cannot be analyzed in any way using the conventional data handling software and hardware tools. If processed judiciously, big data can prove to be a huge advantage for the industries using it. Due to its usefulness, studies are being conducted to create methods to handle the big data. Knowledge extraction from big data is very important. Other than this, there is no purpose for accumulating such volumes of data. Cloud computing is a powerful tool which provides a platform for the storage and computation of massive amounts of data.

Emerging Biomedical Health Care System by Using Internet of Things

2016 ◽  
Vol 27 ◽  
pp. 103-112 ◽  
Author(s):  
Kallam Suresh ◽  
M. Rajasekhara Babu
Keyword(s):  
Health Care ◽  
Big Data ◽  
Data Analysis ◽  
Internet Of Things ◽  
Unstructured Data ◽  
Medical Field ◽  
Digital Device ◽  
Field Interaction ◽  
Device Integration ◽  
User Friendly

Internet of Things and Big Data are critical passion to applying medical field. But both field interaction necessary for Bio Medical fields to improve the Doctor efficiency and it helps to serve patients in better way. In this paper mention that what are the important of the Bio Medical field linking with most recent Technology. Scientific relations to delaying with unstructured data analysis. Digital Device integration requirements for patients. Digital way user friendly communication with Doctor to patient. It helpful for finding disease and counseling patient complications reduce. Finally we achieved a better virtual environment creating with Doctor to patients for improving service.

Security Issues and Challenges Related to Big Data

2021 ◽  
pp. 1604-1620
Author(s):  
Jaimin N. Undavia ◽  
Atul Patel ◽  
Sheenal Patel
Keyword(s):  
Big Data ◽  
Data Analysis ◽  
Database Systems ◽  
Heterogeneous Data ◽  
Unstructured Data ◽  
Huge Amount ◽  
Current Time ◽  
Security Issues ◽  
Future Prediction ◽  
Data Term

Availability of huge amount of data has opened up a new area and challenge to analyze these data. Analysis of these data become essential for each organization and these analyses may yield some useful information for their future prospectus. To store, manage and analyze such huge amount of data traditional database systems are not adequate and not capable also, so new data term is introduced – “Big Data”. This term refers to huge amount of data which are used for analytical purpose and future prediction or forecasting. Big Data may consist of combination of structured, semi structured or unstructured data and managing such data is a big challenge in current time. Such heterogeneous data is required to maintained in very secured and specific way. In this chapter, we have tried to identify such challenges and issues and also tried to resolve it with specific tools.

scholarly journals Unstructured Data Analysis on Big Data Using Map Reduce

2015 ◽  
Vol 50 ◽  
pp. 456-465 ◽  
Author(s):  
V. Subramaniyaswamy ◽  
V. Vijayakumar ◽  
R. Logesh ◽  
V. Indragandhi
Keyword(s):  
Big Data ◽  
Data Analysis ◽  
Unstructured Data ◽  
Map Reduce

Using Term-Based Partitioning Framework on MongoDB and Elastic Search

2014 ◽  
Vol 590 ◽  
pp. 698-701
Author(s):  
Hye Jin Pyo ◽  
Hoon Jeong ◽  
Nan Ju Kim ◽  
Eui In Choi
Keyword(s):  
Big Data ◽  
Data Analysis ◽  
Full Advantage ◽  
Strong Consistency ◽  
Big Data Analysis ◽  
Unstructured Data ◽  
Weak Points ◽  
New Framework

It's a major issue that how can find worthy information in big data. Because big datacan be used in company's success according how to take full advantage of big data analysis. Currently, search technologies aboutbeing stored distributed and duplicated data does not need to strong consistency. Therefore, nowadays we utilize variety of storage based on NoSQL for allowing loosens of strict consistency. MongoDB and Elastic Search have been focused of search and store unstructured data. But they have weak points. So, in this paper, we are going to propose new framework using term-based partitioning which can make up MongoDB and Elastic Search’s limitations.

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