Abstract
The constant advancements in Information Technology have been the main driver of the Big Data concept’s success. With it, new concepts such as Industry 4.0 and Logistics 4.0 are arising. Due to the increase in data volume, velocity, and variety, organizations are now looking to their data analytics infrastructures and searching for approaches to improve their decision-making capabilities, in order to enhance their results using new approaches such as Big Data and Machine Learning. The implementation of a Big Data Warehouse can be the first step to improve the organizations’ data analysis infrastructure and start retrieving value from the usage of Big Data technologies. Moving to Big Data technologies can provide several opportunities for organizations, such as the capability of analyzing an enormous quantity of data from different data sources in an efficient way. However, at the same time, different challenges can arise, including data quality, data management, and lack of knowledge within the organization, among others. In this work, we propose an approach that can be adopted in the logistics department of any organization in order to promote the Logistics 4.0 movement, while highlighting the main challenges and opportunities associated with the development and implementation of a Big Data Warehouse in a real demonstration case at a multinational automotive organization.
Highlights
The explosion of the Information Technologies area has been the driver that launched new concepts such as Big Data and Industry 4.0 into the spotlight
The data model is dynamic and able to change quickly, in order to include more tables, with more information related to any object that already exists in the Big Data Warehouses (BDWs) or to create new ones
This paper presented the proposal and implementation of a BDW in a logistics department of an automotive factory
Summary
The explosion of the Information Technologies area has been the driver that launched new concepts such as Big Data and Industry 4.0 into the spotlight. The financial constraints, the lack of management support, the resistance to change, the lack of infrastructure, and the poor-quality data, among others, are some barriers that need to be faced to implement the concept of Industry 4.0 [4]. This concept relies on the digitization of the production systems to provide the capability of producing customized products within a short time and with costs similar to mass production scenarios [5]. This factor has a tremendous impact on the organizations’ logistics due to the need to react to the sudden changes made by the customers
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