A systems thinking approach to business intelligence solutions based on cloud computing

Thesis (S.M. in System Design and Management)--Massachusetts Institute of Technology, Engineering Systems Division, 2010. === Cataloged from PDF version of thesis. === Includes bibliographical references (p. 73-74). === Business intelligence is the set of tools, processes, practices and people that...

Full description

Bibliographic Details
Main Author: Reyes, Eumir P. (Eumir Paulo Reyes Morales)
Other Authors: John R. Williams.
Format: Others
Language:English
Published: Massachusetts Institute of Technology 2010
Subjects:
Online Access:http://hdl.handle.net/1721.1/59267
Description
Summary:Thesis (S.M. in System Design and Management)--Massachusetts Institute of Technology, Engineering Systems Division, 2010. === Cataloged from PDF version of thesis. === Includes bibliographical references (p. 73-74). === Business intelligence is the set of tools, processes, practices and people that are used to take advantage of information to support decision making in the organizations. Cloud computing is a new paradigm for offering computing resources that work on demand, are scalable and are charged by the time they are used. Organizations can save large amounts of money and effort using this approach. This document identifies the main challenges companies encounter while working on business intelligence applications in the cloud, such as security, availability, performance, integration, regulatory issues, and constraints on network bandwidth. All these challenges are addressed with a systems thinking approach, and several solutions are offered that can be applied according to the organization's needs. An evaluations of the main vendors of cloud computing technology is presented, so that business intelligence developers identify the available tools and companies they can depend on to migrate or build applications in the cloud. It is demonstrated how business intelligence applications can increase their availability with a cloud computing approach, by decreasing the mean time to recovery (handled by the cloud service provider) and increasing the mean time to failure (achieved by the introduction of more redundancy on the hardware). Innovative mechanisms are discussed in order to improve cloud applications, such as private, public and hybrid clouds, column-oriented databases, in-memory databases and the Data Warehouse 2.0 architecture. Finally, it is shown how the project management for a business intelligence application can be facilitated with a cloud computing approach. Design structure matrices are dramatically simplified by avoiding unnecessary iterations while sizing, validating, and testing hardware and software resources. === by Eumir P. Reyes. === S.M.in System Design and Management