Publication Type

Conference Paper

Version

publishedVersion

Publication Date

8-2019

Abstract

With the increasing availabilityof data in the logistics industry due to the digitalization trend, interest andopportunities for leveraging analytics in supply chain management to makedata-driven decisions is growing rapidly. In this paper, we introduce EzLog, anintegrated visualization prototype platform for supply chain analytics. Thisweb-based platform built by two undergraduate student teams for their capstonecourse can be used for data wrangling and rapid analysis of data from differentbusiness units of a major logistics company. Other functionalities of thesystem include standard processes to perform data analysis such as supervisedextraction, transformation, loading (ETL), data type validation and mapping.Weather, real-time stock market and Twitter data can also be collected throughEzLog’s web crawling function, as examples of external data that can be leveragedfor more insights. Aiming to be user-centric, inputs from end-users wereactively pursued in the design of the platform. Easily scalable, Logisticians can access the platform on their machines throughAmazon Web Services (AWS) instances to perform descriptive and predictiveanalysis, including sentiment analysis and topic modeling, to better captureinsights and identify patterns in logistics data.

Keywords

Logistics, Visualization, Web-based application

Discipline

Artificial Intelligence and Robotics | Databases and Information Systems

Research Areas

Intelligent Systems and Optimization

Publication

14th International Congress on Logistics and SCM Systems ICLC 2019, Taipei, Taiwan, August 19-22

Publisher

ACM

City or Country

Taipei, Taiwan

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