Data Analytics in Project Management (Data Analytics Applications) - 9781138307285

Data Analytics in Project Management. Data analytics plays a crucial role in business analytics. Without a rigid approach to analyzing data, there is no way to glean insights from it. Business analytics ensures the expected value of change while that change is implemented by projects in the business environment. Due to the significant increase in the number of projects and the amount of data associated with them, it is crucial to understand the areas in which data analytics can be applied in project management. This book addresses data analytics in relation to key areas, approaches, and methods in project management. It examines: ò Risk management ò The role of the project management office (PMO) ò Planning and resource management ò Project portfolio management ò Earned value method (EVM) ò Big Data ò Software support ò Data mining ò Decision-making ò Agile project management Data analytics in project management is of increasing importance and extremely challenging. There is rapid multiplication of data volumes, and, at the same time, the structure of the data is more complex. Digging through exabytes and zettabytes of data is a technological challenge in and of itself. How project management creates value through data analytics is crucial. Data Analytics in Project Management addresses the most common issues of applying data analytics in project management. The book supports theory with numerous examples and case studies and is a resource for academics and practitioners alike. It is a thought-provoking examination of data analytics applications that is valuable for projects today and those in the future.

• | Author: Seweryn Spalek, J. Davidson Frame, Yanping Chen, Carl Pritchard, Alfonso Bucero, Werner Meyer, Ryan Legard, Michael Bragen, Klas Skogmar, Deanne Larson, Bert Brijs
• | Publisher: Auerbach Publications
• | Publication Date: Oct 24, 2018
• | Number of Pages: 222 pages
• | Language: English
• | Binding: Hardcover/Business & Economics
• | ISBN-10: 1138307289
• | ISBN-13: 9781138307285