JOURNAL ARTICLE

Implementing Online Analytical Processing in Hotel Customer Relationship Management

Muhammad TaufikFaiza RenaldiFajri Rakhmat Umbara

Year: 2021 Journal:   IOP Conference Series Materials Science and Engineering Vol: 1115 (1)Pages: 012040-012040   Publisher: IOP Publishing

Abstract

Abstract Online Analytical Processing (OLAP) is increasingly being used by applying technology concepts that use a multidimensional view of grouping data to provide quick access to strategic information for analysis purposes. In the tourism industry, especially hospitality, this is very useful, especially in processing hotel operational data. Although OLAP technology has been widely applied in the hotel industry in reporting business sales, marketing, and reporting management analysis, there is still little research that discusses customer activity analysis. This study develops an OLAP-based analytical CRM system to analyze customer data and classify it into two main segments: geographically and demographically. Transactional data for hotels that have existed for the last three years are converted into a data warehouse, including the ETL process from the original database to a star schema database. It has a fact table and dimensions. Furthermore, OLAP cube operations are performed and generate customer reports. Testing in this study was carried out by calculating the total data’s access speed and accuracy from 100 to 5000 customers, and the estimated value was 45.50 to 80 milliseconds in 30 experiments. For further research, it can be developed by integrating data from the hotel transactional system so that the analytical process can run in real-time.

Keywords:
Online analytical processing Data warehouse Computer science Transaction data Database Business intelligence Data cube Data science Data mining Database transaction

Metrics

6
Cited By
2.14
FWCI (Field Weighted Citation Impact)
17
Refs
0.88
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Big Data and Business Intelligence
Social Sciences →  Business, Management and Accounting →  Management Information Systems
Customer churn and segmentation
Social Sciences →  Business, Management and Accounting →  Marketing
Data Mining Algorithms and Applications
Physical Sciences →  Computer Science →  Information Systems

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