Real Time Big Data Analytics to Derive Actionable Intelligence in Enterprise Applications

Abstract

Big data is a large-scale data management and analysis technology. The implementation of this technological advantage helps the enterprises and scientific community to concentrate on the innovative transformation. The extraordinary efficacy of this technology surpasses the competency of traditional relational database management system (RDBMS) and bestows diversified computational techniques to steer the storage bottleneck, noise detection, heterogeneous dataset, etc., it entails various analytic and computational methods to extract the actionable insights from the mountains of data accelerated from different causes. Enterprise resource planning (ERP) or systems applications and products (SAP in data processing) framework coordinates key procedures into a solitary framework and improves the complete inventory network by transmitting customer relationship management (CRM) and supply chain management (SCM) arrangements. Despite the fact that numerous business processes accessible in the enterprise, two continuous business use cases of an enterprise are discussed in this paper. The first model is a machine created data processing model. The general design and the outcomes of various analytics cases discussed in this model. The second model is a business arrangement of heterogeneous human-created information model. The data analytics of this model determines this kind of useful data required for decision making in that specific area. It also gives different new perspectives on the big data analytics and computation methodologies. The last segment communicates the challenges of big data.