Presence of big data is a very common phenomenon now days, specially when talking about medium to large size corporation. The term Big Data is often described as vast numbers of data that can be traced, validated, gathered, cached, reengineered, interpreted and also studied. (Manyika, 2011) To clarify they suggested that big data refers to data, whose size makes it impossible to be processed by the typical software used for database management. Also researchers defined big data in terms of its characteristics of high volume, high velocity and high variety (Gartner, 2012) By volume, the researcher referred to the size of the data, by velocity he referred to the speed of which the data is created and by variety he referred to the range of types
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This recruitment process can be a tool used to forecast future employee engagement in the organization. According to the P-O fit theory as discussed in the research paper of Kristof, employees are even more effective when their values, interest and need is on the same track (Kristof, 1996). Therefore, Big Data Management in recruitment can be utilized to analyze the past experience of the applicant to predict the future involvement as a part of commitment. Usually in the past, talent recruitment followed some specific steps where the initial step was to send out a request for an employee, which was triggered by an organizational need (Cappeli, 2001). In the next step, the job description and the requirement for the position are posted on the web portal of the organization (Cappeli, 2001). Later on, interested applicant would apply for the position where they send out their basic profile to the company and share some insights of their past experience along with the educational skill details (Cappeli, 2001). Once they acquire certain number of talents, human resource does some filtering of the profile and selects few profiles to be interviewed. However, in this process, one of the key factors is the experience level of the person who is conducting the interview process. Additional to that, one drawback of the traditional process is the lack of information that is gathered from the applicant’s end and some misleading false information as well. This is when Big Data can come into action and provide some real time and relatively realistic information about the candidates that the organization actually wanted (Zang & Ye,
This recruitment process can be a tool used to forecast future employee engagement in the organization. According to the P-O fit theory as discussed in the research paper of Kristof, employees are even more effective when their values, interest and need is on the same track (Kristof, 1996). Therefore, Big Data Management in recruitment can be utilized to analyze the past experience of the applicant to predict the future involvement as a part of commitment. Usually in the past, talent recruitment followed some specific steps where the initial step was to send out a request for an employee, which was triggered by an organizational need (Cappeli, 2001). In the next step, the job description and the requirement for the position are posted on the web portal of the organization (Cappeli, 2001). Later on, interested applicant would apply for the position where they send out their basic profile to the company and share some insights of their past experience along with the educational skill details (Cappeli, 2001). Once they acquire certain number of talents, human resource does some filtering of the profile and selects few profiles to be interviewed. However, in this process, one of the key factors is the experience level of the person who is conducting the interview process. Additional to that, one drawback of the traditional process is the lack of information that is gathered from the applicant’s end and some misleading false information as well. This is when Big Data can come into action and provide some real time and relatively realistic information about the candidates that the organization actually wanted (Zang & Ye,