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  Here's a nice fact: logistics derives from the Greek word logos, which means reason. According to others, it even stood for "Practical Arithmetic." Currently, a large number of logistics service providers (LSPs) manage a significant flow of products and produce a vast amount of data in the process.  The one thing LSPs need to do is take advantage of the insightful insights the data may offer because they are responsible for millions of shipments every day and millions of related pieces of information. By using this knowledge practically, the holes in logistical operations may be filled. By doing so, we are reintroducing the phrase's reference to practical arithmetic. Until recently, the logistics sector relied on antiquated manual procedures and rigid devices and machinery, missing out on productivity, lucrative prospects, and customer pleasure. But, that is altering.  The popularity of e-commerce, the development of digital technology, and the constant evolution of...

  Introduction The logistics industry could not maximize productivity, profit, or customer satisfaction due to outdated and rigid equipment and machinery. Until recently, this was the situation. However, things are beginning to change. Because of the fast improvements in digital technology, shifting customer preferences, and popularity of e-commerce, logistics is an excellent case study for data science. Using analytics, pertinent data, artificial intelligence (AI), and machine learning would significantly revolutionize the LSP sector (ML). In logistics, for example, data scientists may significantly minimize waste, enhance delivery routes (which may result in lower prices), choose carriers who adhere to best practices for lowering CO2 emissions, and properly estimate supply and demand cycles. Additionally, they can guarantee that dangerous products are handled with the utmost caution. Data scientists are in a position to help humanity benefit from the power of data. Role of Data S...