Deriving a big data analytics framework. Approaching the project management process for big data initiatives

Inhaltsverzeichnis (Table of Contents)

• Abstract
• A. Introduction
  • Background
  • Industry partner
  • Project objective
  • Significance
• B. Research methodology
  • Business Process Management Lifecycle
  • Method overview
  • Literature review
  • Interviews
  • Project management approach for this research project
• C. Results
  • Summary of literature review results
  • Summary of interview findings
  • Big data Analytics Framework
• D. Discussion
• E. Conclusion

Zielsetzung und Themenschwerpunkte (Objectives and Key Themes)

This case study aims to understand best practice project management for big data initiatives and to develop a framework that helps such projects deliver the expected advantages.

• The significance of big data in modern organizations
• Challenges and considerations associated with managing big data initiatives
• Different project management approaches for big data projects
• The development and validation of a Big Data Analytics Framework
• Practical application of the framework for industry partner Red Rocks Company

Zusammenfassung der Kapitel (Chapter Summaries)

• Abstract: This section introduces the case study's objective, which is to investigate the project management approach for big data projects at Red Rocks Company. It highlights the importance of big data for future decision-making and process automation and discusses the challenges associated with delivering expected benefits due to the novelty of the topic. The study involves a literature review to identify existing approaches and interviews with industry stakeholders to validate the findings.
• A. Introduction: This section delves into the background of big data, its importance for organizational competitiveness, and the challenges associated with its implementation. It also introduces the industry partner, Red Rocks Company, and their specific needs and goals related to big data. The project objectives and significance are outlined, emphasizing the practical benefits for the company and the broader research community.
• B. Research methodology: This section explains the research approach adopted in the study. It details the Business Process Management (BPM) Lifecycle model used as a framework for the research process. The methodology encompasses literature review, interviews with industry stakeholders, and a specific project management approach tailored to this research project.
• C. Results: This section presents the key findings of the research. It summarizes the literature review on different project management approaches for big data initiatives, including Waterfall, Agile, CRISP-DM, and hybrid approaches. It also presents the findings from the interviews with industry stakeholders, focusing on their experiences and perspectives on managing big data projects. The section then introduces the developed Big Data Analytics Framework, which integrates the insights gained from the literature review and interviews.

Schlüsselwörter (Keywords)

This case study focuses on project management for big data initiatives, exploring key topics like business process management, CRISP-DM framework, agile and waterfall methodologies, and interview-based validation. The study delivers valuable insights for organizations seeking to leverage big data effectively and aims to contribute to the growing body of knowledge on big data project management.