222 pages | 30 B/W Illus.
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.
Introduction - Seweryn Spalek
Why Data Analytics in Project Management? - J. Davidson Frame, Yanping Chen
Data Analytics Risk – Lost in Translation? - Carl Pritchard
Analytical Challenges of a Modern PMO - Seweryn Spalek
Data Analytics and Project Portfolio Management - Alfonso Bucero
Earned Value Method - Werner Meyer
How to Manage Big Data Issues in a Project Environment - Ryan Legard
IT Solutions of Data Analytics as Applied to Project Management - Michael Bragen
Conventional and Unconventional Data Mining for Better Decision Making - Klas Skogmar
Agile Project Management and Data Analytics - Deanne Larson
Data Analytics and Scrum -Bert Brijs