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Big Data for Managers - A Study to Define the Concept and Highlight its Challenges

Dobrzanski, Maciej LU and Mukherjee, Annwesh LU (2017) MGTN59 20171
Department of Business Administration
Abstract
Purpose: The purpose of the study was to understand the key managerial challenges associated with Big Data. The research aimed to look at the possible obstacles that managers need to overcome while implementing Big Data. The main research question is : What are the main managerial challenges associated with Big Data and what steps are needed to overcome those?
Methodology: Based on the concepts of relativism and constructionism, the research focused on an inductive approach to find the challenges faced by companies using Big Data. The research also covered a view of a company that is planning to use it. Qualitative data collection method was used in the project and empirical data was collected through unstructured and semi-structured... (More)
Purpose: The purpose of the study was to understand the key managerial challenges associated with Big Data. The research aimed to look at the possible obstacles that managers need to overcome while implementing Big Data. The main research question is : What are the main managerial challenges associated with Big Data and what steps are needed to overcome those?
Methodology: Based on the concepts of relativism and constructionism, the research focused on an inductive approach to find the challenges faced by companies using Big Data. The research also covered a view of a company that is planning to use it. Qualitative data collection method was used in the project and empirical data was collected through unstructured and semi-structured interviews. The interviews were conducted on managers and leaders from different companies partly through opportunistic sampling and partly through snowball sampling.
Findings: Defining the phenomenon of Big Data turned out to be a difficult task. Understanding the underlying concepts that characterize it proved to be challenging as well. A lot of empirical data was put to analysis and the result showed that there are several managerial challenges that need to be understood. Finding the right technology, judging and making use of the right competence, considering the duration it would take to get it started and recognizing the integrity and privacy issues related to it brought together formed an integrated model which can be used by managers.
Limitations: The idea of Big Data is found to be contextual and it varies from one company to another. Since the concept is new and is being developed there were not many literary articles or material found on this topic. The research could not therefore work on a deep knowledge base. The empirical data is collected from companies which are mostly based in the Skåne region of Sweden. The variety of the empirical data
ii
suffer from the fact that there was not much time to collect it from other parts of the world.
Practical implication: The theoretical discussions and the insights from the literature could act as a guide for managers who was already using or are planning to use Big Data. The challenges that became visible from the interview data are useful for managers. Furthermore, the integrated model presented as outcome of this research can be valuable for managers and leaders working with Big Data. (Less)
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author
Dobrzanski, Maciej LU and Mukherjee, Annwesh LU
supervisor
organization
course
MGTN59 20171
year
type
H1 - Master's Degree (One Year)
subject
language
English
id
8917039
date added to LUP
2017-06-19 12:16:39
date last changed
2017-06-19 12:16:39
@misc{8917039,
  abstract     = {Purpose: The purpose of the study was to understand the key managerial challenges associated with Big Data. The research aimed to look at the possible obstacles that managers need to overcome while implementing Big Data. The main research question is : What are the main managerial challenges associated with Big Data and what steps are needed to overcome those?
Methodology: Based on the concepts of relativism and constructionism, the research focused on an inductive approach to find the challenges faced by companies using Big Data. The research also covered a view of a company that is planning to use it. Qualitative data collection method was used in the project and empirical data was collected through unstructured and semi-structured interviews. The interviews were conducted on managers and leaders from different companies partly through opportunistic sampling and partly through snowball sampling.
Findings: Defining the phenomenon of Big Data turned out to be a difficult task. Understanding the underlying concepts that characterize it proved to be challenging as well. A lot of empirical data was put to analysis and the result showed that there are several managerial challenges that need to be understood. Finding the right technology, judging and making use of the right competence, considering the duration it would take to get it started and recognizing the integrity and privacy issues related to it brought together formed an integrated model which can be used by managers.
Limitations: The idea of Big Data is found to be contextual and it varies from one company to another. Since the concept is new and is being developed there were not many literary articles or material found on this topic. The research could not therefore work on a deep knowledge base. The empirical data is collected from companies which are mostly based in the Skåne region of Sweden. The variety of the empirical data
ii
suffer from the fact that there was not much time to collect it from other parts of the world.
Practical implication: The theoretical discussions and the insights from the literature could act as a guide for managers who was already using or are planning to use Big Data. The challenges that became visible from the interview data are useful for managers. Furthermore, the integrated model presented as outcome of this research can be valuable for managers and leaders working with Big Data.},
  author       = {Dobrzanski, Maciej and Mukherjee, Annwesh},
  language     = {eng},
  note         = {Student Paper},
  title        = {Big Data for Managers - A Study to Define the Concept and Highlight its Challenges},
  year         = {2017},
}