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

A case study

Master's Thesis , 2018 , 44 Pages , Grade: 7

Computer Science - Commercial Information Technology

This thesis investigates the project management approach for big data projects for industry partner Red Rocks Company. The aim of this project is to understand best practice project management for big data initiatives and to develop a framework to help such projects to deliver the expected advantages. A brief literature review is undertaken to find out how big data projects are managed. From this, a Big Data Analytics Framework is derived which is based on CRISP-DM. The framework is validated through interviews with stakeholders from the corporate sector. For this case study, the first three phases of the Business Process Management Lifecycle are applied: process discovery, analysis and design.

Key findings of the case study are that literature recommends an agile project management approach for big data initiatives. On the contrary, the majority of interviewed industry stakeholders confirmes a waterfall approach is conducted more often to deliver such projects. The developed Big Data Analytics Framework will add significant benefits to Red Rocks Company as it will help to successfully deliver big data initiatives in future. Big data is considered a key enabler for future decision making and process automation. The topic is however very new and not well understood yet. Hence 50% of big data projects are not delivering the expected benefits and are costing more than initially planned.

Contents

Abstract

A. Introduction
Background
Industry partner
Project objective
Significance

B. Research methodology
Business Process Management Lifecycle
Method overview
Literature review
Phase 1 - Extraction of literature
Phase 2 – Organization and preparation for analysis of artefacts
Phase 3 – Coding and analysis
Phase 4 – Write up and presentation
Interviews
Project management approach for this research project

C. Results
Summary of literature review results
Waterfall approach
Agile
CRISP-DM
Hybrid agile and waterfall approach
Summary of interview findings
Big data Analytics Framework
1. Business Understanding
2. Understand and Prepare Data
3. Validate Business Understanding
4. Design Solution
5. Evaluate Solution
6. Validate Business Understanding
7. Deployment

D. Discussion

E. Conclusion

Abbreviations

References

Appendix 1 – Reflection of learnings and project logs

Appendix 2 – Literature review details

Appendix 4 - Questionnaire

Appendix 5 – Transcript interview

Appendix 6 – Transcript interview

Appendix 7 – Transcript interview

Appendix 8 – Transcript interview

Appendix 9 – Transcript interview

• College: Queensland University of Technology (Faculty of Science and Engineering)
• Course: Master in Business Process Management
• Grade: 7
• Author: Theres Mitscherling (Author)
• Publication Year: 2018
• Pages: 44
• Catalog Number: V499625
• ISBN (eBook): 9783346033536
• ISBN (Book): 9783346033543
• Language: English
• Tags: BigData, ProjectManagement, Agile, BigDataAnalytics, Waterfall, CRISPDM, Mining, AustralianMining, AustralianMiningIndustry