Integration of Spark framework in Supply Chain Management

There has been a big boom in the field of supply chain management. With almost all the processes related to supply chain are being carried out digitally the data has expanded to a limit where in it has to handled meticulously. Handling and extracting such an intricate widespread information big data analytics is the only rescue to resort to. Big data analysis runs on the Hadoop framework so far which allows an organization to store large quantity of data on disc and also process it. Due to increase in demand for data analytics, specifically speaking faster data analytics framework Hadoop is considered to be not fast enough. This is where Apache Spark came into picture 18 months ago. Apache Spark is termed to be 100 times faster than Hadoop and this allows an organization to process the same big data in a shorter span of time thus, addressing the increasing demand effectively. In this research paper we put forward the details about the Apache Spark framework while comparing it with the existing Hadoop framework alongside, how using Apache Spark framework in Supply chain management for data analytics would benefit the organization and businesses. (C) 2016 The Authors. Published by Elsevier B.V.