ABSTRACT
A goal of knowledge management (KM) is to capture and share knowledge wherever it resides in the organization. Leveraging the corporate collective know-how will improve decision making and innovation where it is needed. The proliferation of data, information, and knowledge has created a phenomenon called Big Data. KM when applied to Big Data will enable a type of analysis that will uncover the complete picture of the organization and be a catalyst for driving decisions. In order to leverage an organization’s Big Data, must be broken down into smaller more manageable parts. This will facilitate a succinct analysis, which can then be regrouped with other smaller subsets to produce big picture results. Volume, velocity, and variety are all aspects that define Big Data.
Volume: It is the proliferation of all types of data expanding to many terabytes of information.
Velocity: It is the ability to process data quickly.
Variety: It refers to the different types of data (structured and unstructured data such as data in databases, content in content management and KM systems/repositories, collaborative environments, blogs, wikis, sensor data, audio, video, click streams, and log files). Variety is the component of Big Data in which KM will play a major role in driving decisions. Enterprises need to be able to combine their analyses to include information from both structured databases and unstructured content.
