Using Big Data to Manage Human Resources

Big Data ◽  
2014 ◽  
pp. 184-197
Keyword(s):  
Big Data ◽  
Human Resources

scholarly journals Using the Big Data in the human resources management systems

2018 ◽  
Vol 8 (3) ◽  
pp. 129-133
Author(s):  
Goker Oge ◽  
Murat Topaloglu
Keyword(s):  
Big Data ◽  
Human Resources ◽  
Programming Languages ◽  
File System ◽  
Labour Force ◽  
Human Resources Management ◽  
Data Entry ◽  
Resources Management ◽  
Personnel Recruitment ◽  
System File

Measures like setting a destination, evaluation of performances, planning of the labour force about business, personnel recruitment, charging of personnel, informations about personnel, analytical of labour force and reporting, etc., are considered as vital problems of the human resources management. In this study, these criteria in a variety of data were collected with a large repository Apache Hadoop Distributed File System file system owned. Data entry and analysis were used Apache Pig and Java programming languages. The aim of the study is to help ‘the owners of business’ evaluate the abundance of data and to get rid of the management complexity via an application which is the biggest problem of management system in human resources. Keywords: Big Data, management of human resources, Hadoop, Pig, map-reduce

scholarly journals Human resources for Big Data professions: A systematic classification of job roles and required skill sets

2018 ◽  
Vol 54 (5) ◽  
pp. 807-817 ◽  
Author(s):  
Andrea De Mauro ◽  
Marco Greco ◽  
Michele Grimaldi ◽  
Paavo Ritala
Keyword(s):  
Big Data ◽  
Human Resources ◽  
Systematic Classification ◽  
Skill Sets ◽  
Job Roles

scholarly journals Implementasi Sistem Interkoneksi Basis Data Terdistribusi Menggunakan Socket API

2017 ◽  
Vol 1 (1) ◽  
pp. 1-4
Author(s):  
Ary Yulianto
Keyword(s):  
Information System ◽  
Big Data ◽  
Human Resources ◽  
Distributed Databases ◽  
Distributed Database ◽  
Database System ◽  
Master Data ◽  
Distributed Database System ◽  
The Moment ◽  
Asset Data

  Majelis Pendidikan Dasar dan Menengah Pimpinan Daerah Kabupaten Magelang needs information about the development of the school. The necessary data include data on human resources, asset data and data of their students. At the moment the data is obtained manually by looking to the schools. With the development of information technology is now expected to have a school information system that can provide information quickly and accurately. Data on each school if put into one large server or big data can be used to analyze the data. The purpose of this research is to implement the interconnection of distributed database system using the socket API. It is used to provide master data of all schools under Persyarikatan Muhammadiyah. To support the analysis of the data interconnection of distributed databases, socket API technology is used. With a system like this then the communications database can be connected so that the school's data will be sent directly through the socket API and the data will automatically be processed by the webservice in the server middleware and will be utilized in the next process.

scholarly journals Parallel Classification Algorithm Design of Human Resource Big Data Based on Spark Platform

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Wang Zhouhuo
Keyword(s):  
Big Data ◽  
Human Resources ◽  
Human Resource ◽  
Data Clustering ◽  
Ant Colony Algorithm ◽  
Algorithm Design ◽  
Large Data ◽  
Classification Algorithm ◽  
Classification Rule ◽  
Fuzzy Genetic

In order to solve the problem of large data classification of human resources, a new parallel classification algorithm of large data of human resources based on the Spark platform is proposed in this study. According to the spark platform, it can complete the update and distance calculation of the human resource big data clustering center and design the big data clustering process. Based on this, the K-means clustering method is introduced to mine frequent itemsets of large data and optimize the aggregation degree of similar large data. A fuzzy genetic algorithm is used to identify the balance of big data. This study adopts the selective integration method to study the unbalanced human resource database classifier in the process of transmission, introduces the decision contour matrix to construct the anomaly support model of the set of unbalanced human resource data classifier, identifies the features of the big data of human resource in parallel, repairs the relevance of the big data of human resource, introduces the improved ant colony algorithm, and finally realizes the design of the parallel classification algorithm of the big data of human resource. The experimental results show that the proposed algorithm has a low time cost, good classification effect, and ideal parallel classification rule complexity.

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