Challenges and Potential Solutions for Big Data Implementations in Developing Countries

Abstract

BACKGROUND: The volume of data, the velocity with which they are generated, and their variety and lack of structure hinder their use. This creates the need to change the way information is captured, stored, processed, and analyzed, leading to the paradigm shift called Big Data. OBJECTIVES: To describe the challenges and possible solutions for developing countries when implementing Big Data projects in the health sector. METHODS: A non-systematic review of the literature was performed in PubMed and Google Scholar. The following keywords were used: "big data", "developing countries", "data mining", "health information systems", and "computing methodologies". A thematic review of selected articles was performed. RESULTS: There are challenges when implementing any Big Data program including exponential growth of data, special infrastructure needs, need for a trained workforce, need to agree on interoperability standards, privacy and security issues, and the need to include people, processes, and policies to ensure their adoption. Developing countries have particular characteristics that hinder further development of these projects. CONCLUSIONS: The advent of Big Data promises great opportunities for the healthcare field. In this article, we attempt to describe the challenges developing countries would face and enumerate the options to be used to achieve successful implementations of Big Data programs.

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