Implementation of Business Intelligence in Data Superstore Sales with Online Analytical Processing Method

Authors

    Dandy dandy( 1 ) Rino Rino( 2 )

    (1) Universitas Buddhi Dharma
    (2) Universitas Buddhi Dharma

DOI:


https://doi.org/10.32877/bt.v3i2.182

Keywords:


Business Intelligence, Business Intelligence Roadmap, OLAP, Superstore Sales

Abstract

Transaction data in superstore sales data are very useful for company development, can be used to describe and forecast or predict future sales transaction data and to study the past about business opportunities and challenges. The use of Business Intelligence (BI) technology can help analyze large amounts of data, in addition, BI is a powerful tool for quality analysis and company analysis. This study designed an information system using the BI approach to analyze transaction data on superstore sales data. The research focus is on report data, namely superstore sales data regarding sales transactions. This study uses the OLAP method to describe data visualization so that it provides benefits and competitive advantages. This system can improve the quality of decisions taken in solving the problem of abundant data accumulation, monitoring operational activities, fulfilling information needs and effective data management. Business intelligence is expected for company leaders to be able to understand the data that will have been processed in understanding visual forms and can easily absorb the information needed to make decisions for the company. In addition, with the design of website-based business intelligence that is effective and efficient to produce opportunities in making decisions to predict the increase or decrease that will occur in the coming years using the histories in the superstore sales data of the previous years

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Published

2021-04-18

How to Cite

[1]
D. dandy and R. Rino, “Implementation of Business Intelligence in Data Superstore Sales with Online Analytical Processing Method”, bit-Tech, vol. 3, no. 2, pp. 44–50, Apr. 2021.

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Section

Articles
DOI : https://doi.org/10.32877/bt.v3i2.182
Abstract views: 506 / PDF downloads: 584