Table of Contents
Big data can be best defined as the capture, curation, storage, search and analysis of large and complex data sets which are generally difficult to be processed or handled by traditional data processing systems. These systems are currently being implemented on a limited scale in many supply chain companies for varied purposes. Most supply chain companies on an average use more than two systems for management purposes. Some have two instances of Enterprise Resource Planning (ERP) software installed for different parts of the supply chain and logistics purposes. Different use cases for the systems are order management; demand planning, warehouse management, price management, production planning, tactical supply planning, transportation planning, product lifecycle management and Manufacturing Execution Systems (MES). This is one major reason for the utilization of Big data in companies. Other in-depth reasons for the need for Big data in SCM have been covered in the report.
Companies for example need to anticipate problems or understand growth through the usage of advanced analytics. Traditional business analytics can answer the questions that leaders know to ask. But the questions that are important but companies do not know to ask are more crucial to build risk mitigation strategies. An important question for example can be about the ways to learn about product and service failures in the market which can be asked and answered through use of Big data predictive analysis. Text mining and rules-based ontologies are some of the techniques which can be used to build listening capabilities to learn early and mitigate issues quickly.
This report discusses the key players in the Big data market by their types of software and solution offerings. The overall Big data market has been segmented into key industry verticals and by the geographic regions on a global scale. The need for Big data in supply chain management has been discussed in detail with the key market drivers, market restraints and opportunities presented in this context. The investment scenario, collaborations and joint ventures of Big data companies has been covered in in-depth analysis to give an insight into the rising interest in Big data players from across the private and government entities.
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