• VAIBHAVI RAJARAM GOLGIRE

Big data refers to vast quantities of data from multiple sources in various formats. Because of the versatility of the supply chain industry to volume, data generation speed and a variety of data, Data analysis and knowledge using traditional methods is difficult. Data analysis includes the discovery of useful knowledge from large data sets to support decision-making including data review, cleaning, transformation and modelling. Many big data and analysis tools have made it possible for people to gain precious insights from this vast volume of data. Data analytics will help forecast the supply chain industry that is our leading customers, future consumer demand, product design insight, attractive functions, system failure prediction, and much more. This thesis explores the application of Big Data Analytics in logistics and management of supply chains. Importance of new technologies for database management, including MongoDB, DB2, MarkLogic and Apache Cassandra, various ETL tools, such as SSIS, Informatica, Talend, Ab Initio, data replication and recovery. Conventional relation databases are not appropriate for storing this vast amount and variety of data, so scalable databases such as Apache HBase that accommodate large volumes of data using clusters and NoSQL systems have to be used. The use of these advanced technology enables the company to make effective and efficient decision-making that reduces its operating costs. Open research issues in this area includes data protection and safety problems, big data efficiency and scalability, lack of resources.

supply chain management, logistics, Big data

"Big data analytics and machine learning in logistics and supply chain management: analysis, optimization and future scope", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.8, Issue 5, page no.g388-g393, May-2021, Available :http://www.jetir.org/papers/JETIR2105850.pdf

"Big data analytics and machine learning in logistics and supply chain management: analysis, optimization and future scope", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.8, Issue 5, page no. ppg388-g393, May-2021, Available at : http://www.jetir.org/papers/JETIR2105850.pdf