Research on the effective usage of Information and Communication Technologies for Development, suggests that big data technology can make important contributions but also present unique challenges to international development. Advancements in big data analysis offer cost-effective opportunities to improve decision-making in critical development areas such as health care, employment, economic productivity, crime, security, and natural disaster and resource management. However, longstanding challenges for developing regions such as inadequate technological infrastructure and economic and human resource scarcity exacerbate existing concerns with big data such as privacy, imperfect methodology, and interoperability issues.
Big data can be described by the following characteristics:
Volume – The quantity of data that is generated is very important in this context.It is the size of the data which determines the value and potential of the data under consideration and whether it can actually be considered as Big Data or not.The name ‘Big Data’ itself contains a term which is related to size and hence the characteristic.
Variety - The next aspect of Big Data is its variety.This means that the category to which Big Data belongs to is also a very essential fact that needs to be known by the data analysts.This helps the people, who are closely analyzing the data and are associated with it, to effectively use the data to their advantage and thus upholding the importance of the Big Data.
Velocity - The term ‘velocity’ in the context refers to the speed of generation of data or how fast the data is generated and processed to meet the demands and the challenges which lie ahead in the path of growth and development.
Variability - This is a factor which can be a problem for those who analyze the data. This refers to the inconsistency which can be shown by the data at times, thus hampering the process of being able to handle and manage the data effectively.
Veracity - The quality of the data being captured can vary greatly. Accuracy of analysis depends on the veracity of the source data.
Complexity - Data management can become a very complex process, especially when large volumes of data come from multiple sources. These data need to be linked, connected and correlated in order to be able to grasp the information that is supposed to be conveyed by these data. This situation, is therefore, termed as the ‘complexity’ of Big Data.
Big data is an all-encompassing term for any collection of data sets, so large and complex that it becomes difficult to process using traditional data processing applications. The challenges include analysis, capture, search, sharing, storage, transfer, visualization, and privacy violations. The trend to larger data sets is due to the additional information derivable from analysis of a single large set of related data, as compared to separate smaller sets with the same total amount of data, allowing correlations to be found to “spot business trends, prevent diseases, combat crime and so on.”