A Holistic View of Big Data

Big Data ◽  
2016 ◽  
pp. 73-84 ◽  
Author(s):  
Won Kim ◽  
Ok-Ran Jeong ◽  
Chulyun Kim

Today there is much hype about big data. The discussions seem to revolve around data mining technology, social Web data, and the open source platform of NoSQL and Hadoop. However, database, data warehouse and OLAP technologies are also integral parts of big data. Big data involves data from all sources, not just social Web data. Further, big data requires not only technology, but also a painstaking process for identifying, collecting, and preparing sufficient amounts of relevant data. This paper provides a holistic view of big data.

2014 ◽  
Vol 10 (3) ◽  
pp. 59-69 ◽  
Author(s):  
Won Kim ◽  
Ok-Ran Jeong ◽  
Chulyun Kim

Today there is much hype about big data. The discussions seem to revolve around data mining technology, social Web data, and the open source platform of NoSQL and Hadoop. However, database, data warehouse and OLAP technologies are also integral parts of big data. Big data involves data from all sources, not just social Web data. Further, big data requires not only technology, but also a painstaking process for identifying, collecting, and preparing sufficient amounts of relevant data. This paper provides a holistic view of big data.


2019 ◽  
Vol 23 (2) ◽  
pp. 42-49 ◽  
Author(s):  
K. V. Mulyukova ◽  
V. M. Kureichik

The purpose of the work is to study the current problems and prospects of the solution for processing big data received or stored in the Internet (web data), as well as the possibility of practical realization of Data Mining technology for big web data on practical example. Materials and methods. The study included a review of bibliographic sources on big data analysis problems.Data Mining technology was used to analyze large web data, as well as computer modeling of a practical problem using the C # programming language and creating a DDL database structure for accumulating web data.Results. In the course of the work, the specifics of big data were described, the main characteristics of big data were highlighted, and modern approaches to processing big data were analyzed. A brief description of the horizontal-scalable architecture and the BI-solution architecture for big data processing is given. The problems of processing large web data are formulated: limiting the speed of access to data, providing access via network protocols through general-purpose networks.An example showing the approach to processing large web data was also implemented. Based on the idea of big data, the described complexities of web data processing and the methods of Data Mining, techniques were proposed for effectively solving the practical problem of processing and searching patterns in a large data array.The following classes have been developed in the C # programming language:Class of receiving web data via the Internet; Data conversion class;Intelligent data processing class;Created DDL script that creates a structure for the accumulation of web data.A single UML class diagram has been developed.The constructed system of data and classes allows to solve the main part of the problems of processing large web data and perform intelligent processing using Data Mining technology in order to solve the problem posed of identifying certain records in a large array. The combination of object-oriented approach, neural networks and BI-analysis to filter data will speed up the process of data processing and obtaining the result of the studyConclusion. According to the results of the study, it can be argued that the current state of technology for analyzing large web data allows you to efficiently process data objects, identify patterns, get hidden data and get full-fledged statistical data.The obtained results can be used both for the purpose of the initial study of big data processing technologies, and as a basis for developing an already real application for analyzing web data. The use of neural networks and the created universal classes-handlers makes the created architecture flexible and self-learning, and the class declarations and the base DDL structure will greatly simplify the development of program code.


2014 ◽  
Vol 496-500 ◽  
pp. 2108-2111
Author(s):  
Jian Hu Zhang ◽  
Lei Lei ◽  
Xin You Cui ◽  
Yong Wu ◽  
Lin Tao Li

Through in-depth understanding of the domain knowledge of insurance and the study of the technology of data warehouse, the paper illustrate the application of data mining technology and data warehouse technology in the insurance clients analysis, and from the basic flow of, discusse the application of data warehouse technology in the field of insurance industry. Then, from the concept of data warehouse, describe the design and implementation of data warehouse concept model and logical model.


2020 ◽  
pp. 1-10
Author(s):  
Yuejun Xia

Artificial intelligence model combined with data mining technology can mine useful data from college ideological and political education management, and conduct process evaluation and teaching management. Therefore, based on the superiority of data mining technology and artificial intelligence system, this paper improves the traditional algorithm and constructs a university ideological and political education management model based on big data artificial intelligence. Moreover, this study uses a local sensitive hash function to generate representative point sets and uses the generated representative point sets for clustering operations. In order to verify the performance of the algorithm model, a control experiment is designed to compare the algorithm of this paper with traditional data mining methods. It can be seen from the research results that the algorithm model constructed in this paper has good performance and can be applied to practice.


2016 ◽  
Vol 07 (03) ◽  
pp. 31-33
Author(s):  
ATIF AZIZ ◽  
◽  
RAJEEV ARYA ◽  
SANA SHAFIQUE ◽  
◽  
...  

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