RFID Data Warehousing and OLAP with Hive
Yeisol Yoo, Jin Soung Yoo · 2019
Radio Frequency Identification (RFID) technology is used in many applications for monitoring object movement. The use of RFID in supply chain management systems enables to track the movement of products from suppliers to warehouses, store backrooms, and eventually points of sale. The vast amount of data resulting from the proliferation of RFID readers and tags poses challenges for data management and analytics. RFID data warehousing can enhance data quality and consistency, and give great potential benefits for Online Analytical Processing (OLAP) applications. Traditional data warehouses are built primarily on relational database management systems. However, the size of RFID data being collected and analyzed in the industry for business intelligence is growing rapidly, making traditional warehousing solutions prohibitively expensive. Hive is an open-source data warehousing solution built on top of Hadoop which is a popular Big Data computing framework. This paper presents alternative RFID data warehouse designs which can handle a large amount of RFID data and support a variety of OLAP queries. The proposed approaches are implemented on Hive and evaluated for query performance in cloud computing environment.