Data analytics in project management

Description

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. Content: Introduction - Seweryn SpalekWhy Data Analytics in Project Management? - J. Davidson Frame, Yanping ChenData Analytics Risk - Lost in Translation? - Carl PritchardAnalytical Challenges of a Modern PMO - Seweryn SpalekData Analytics and Project Portfolio Management - Alfonso BuceroEarned Value Method - Werner MeyerHow to Manage Big Data Issues in a Project Environment - Ryan LegardIT Solutions of Data Analytics as Applied to Project Management - Michael BragenConventional and Unconventional Data Mining for Better Decision Making - Klas SkogmarAgile Project Management and Data Analytics - Deanne LarsonData Analytics and Scrum -Bert Brijs