(Ebook PDF) Data Analytics in Project Management 1st edition by Seweryn Spalek 1138307289 978-1138307285 full chapters

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1138307289, 978-1138307285

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Product details:

ISBN-10 : 1138307289

ISBN-13 : 978-1138307285

Author: Seweryn Spalek

This book aims to help the reader better understand the importance of data analysis in project management. Moreover, it provides guidance by showing tools, methods, techniques and lessons learned on how to better utilize the data gathered from the projects. First and foremost, insight into the bridge between data analytics and project management aids practitioners looking for ways to maximize the practical value of data procured. The book equips organizations with the know-how necessary to adapt to a changing workplace dynamic through key lessons learned from past ventures. The book’s integrated approach to investigating both fields enhances the value of research findings.

Data Analytics in Project Management 1st Table of contents:

1. Chapter 1: Introduction – Recognizing Data Analysis as Integral to Successful 
Project Management. 
2. Chapter 2: Why Data Analytics in Project Management? – Exploring the 
Imperative of Data Analysis. 
3. Chapter 3: Data Analytics Risk: Lost in Translation? – Unraveling Risks and the 
Role of Data Analysis. 
4. Chapter 4: Analytical Challenges of a Modern PMO – Addressing the Role and 
Hurdles of Data Analysis within the PMO. 
5. Chapter 5: Data Analytics and Project Portfolio Management – Emphasizing 
Decision-Making Metrics. 
6. Chapter 6: Earned Value Method – Analyzing EVM for Project Management. 
7. Chapter 7: How to Manage Big Data Issues in a Project Environment – 
Strategies for Navigating Big Data Challenges. 
8. Chapter 8: IT Solutions of Data Analytics as Applied to Project Management – A 
Detailed Case Study. 
9. Chapter 9: Conventional and Unconventional Data Mining for Better Decision 
Making – Harnessing Data Mining for Enhanced Decision Making. 
10. Chapter 10: Agile Project Management and Data Analytics – Exploring Agile 
Values and Processes. 
11. Chapter 11: Data Analytics and Scrum – Navigating the Convergence and 
Divergence of Scrum and Data Analytics.

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