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Master's Thesis from the year 2018 in the subject Computer Science - Commercial Information Technology, grade: 7, Queensland University of Technology (Faculty of Science and Engineering), course: Master in Business Process Management, language: English, abstract: 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.
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- EditoreGRIN Verlag
- Data di pubblicazione2020
- ISBN 10 3346033546
- ISBN 13 9783346033543
- RilegaturaCopertina flessibile
- LinguaInglese
- Numero edizione1
- Numero di pagine28
- Contatto del produttorenon disponibile
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Deriving a big data analytics framework. Approaching the project management process for big data initiatives
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Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Master's Thesis from the year 2018 in the subject Computer Science - Commercial Information Technology, grade: 7, Queensland University of Technology (Faculty of Science and Engineering), course: Master in Business Process Management, language: English, abstract: 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. 28 pp. Englisch. Codice articolo 9783346033543
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Deriving a big data analytics framework. Approaching the project management process for big data initiatives : A case study
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Taschenbuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - Master's Thesis from the year 2018 in the subject Computer Science - Commercial Information Technology, grade: 7, Queensland University of Technology (Faculty of Science and Engineering), course: Master in Business Process Management, language: English, abstract: 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. Codice articolo 9783346033543
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Deriving a big data analytics framework. Approaching the project management process for big data initiatives
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Taschenbuch. Condizione: Neu. Neuware -Master's Thesis from the year 2018 in the subject Computer Science - Commercial Information Technology, grade: 7, Queensland University of Technology (Faculty of Science and Engineering), course: Master in Business Process Management, language: English, abstract: 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.Books on Demand GmbH, Überseering 33, 22297 Hamburg 28 pp. Englisch. Codice articolo 9783346033543
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Deriving a big data analytics framework. Approaching the project management process for big data initiatives: A case study
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Deriving a big data analytics framework. Approaching the project management process for big data initiatives | A case study
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Taschenbuch. Condizione: Neu. Deriving a big data analytics framework. Approaching the project management process for big data initiatives | A case study | Theres Mitscherling | Taschenbuch | Paperback | 28 S. | Englisch | 2020 | GRIN Verlag | EAN 9783346033543 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu. Codice articolo 118005252
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