Improving Project Management Decisions With Big Data Analytics

Author:

Jamil George Leal1,Carvalho Luiz Fernando Magalhães2

Affiliation:

1. Informações em Rede C e T Ltda., Brazil

2. Banco Itaú, Brazil

Abstract

A relationship between project management and knowledge management was observed with a detailed level of analysis in this chapter, as analytics tools and methods were presented to define new perspectives for these dynamics. After a theoretical review that advanced the level reached by a previous paper on the same topic a new theoretical background was completely worked, resulting in a base where a deeper way of analysis allowed, at the end, to study practical cases of rich association for PM and KM in practical, ready to apply situations. As a trend for next competitive cycles, tools, methods, and techniques that focus knowledge production for decision making are to be increasingly defined and applied, on one hand enabling organizations to propose new competitive structures and positioning, and on the other hand, presenting a more aggressive, faster, and demanding competitive environment.

Publisher

IGI Global

Reference69 articles.

1. Azevedo, A., & Lourenço, A. (2008). KDD, SEMMA and CRISP-DM: a parallel overview. Available at http://hdl.handle.net/10400.22/136

2. Firm Resources and Sustained Competitive Advantage

3. Twitter mood predicts the stock market

4. Boyd, D., & Crawford, K. (2011). Six provocations for Big Data. Annals of “A decade in Internet time: Symposium on the dynamics of the internet and society”.

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