Effective Demand Forecasting Model Using Business Intelligence Empowered With Machine Learning
In the modern era business intelligence (BI) has a pivotal role in articulating a strategy and taking correct measures based on data. Business intelligence plays a pivotal role in an inevitable decision support system that enables the enterprise to perform analysis on data and throughout the process...
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| Veröffentlicht in: | IEEE access 2020, Vol.8, p.116013-116023 |
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| creator | Khan, Muhammad Adnan Saqib, Shazia Alyas, Tahir Ur Rehman, Anees Saeed, Yousaf Zeb, Asim Zareei, Mahdi Mohamed, Ehab Mahmoud |
| description | In the modern era business intelligence (BI) has a pivotal role in articulating a strategy and taking correct measures based on data. Business intelligence plays a pivotal role in an inevitable decision support system that enables the enterprise to perform analysis on data and throughout the process of business. Machine learning predicts the forecasting of future demands of the enterprises. Demand forecasting is one of the main decision-making tasks of enterprise. For demand forecasting first raw sales data is collected from the market, then according to data, the future sale/product demands are forecasted. This prediction is based on collected data that compiles through different sources. The machine learning engine executes data from different modules and determines the weekly, monthly, and quarterly demands of goods/commodities. In demand forecasting, its perfect accuracy is non-compromising, the more accurate system model is more efficient. Furthermore, we test the efficiency by comparing the predicted data with actual data and determine the percentage error. Simulation results show that after applying the purposed solution on real-time organization data, we get up to 92.38 % accuracies for the store in terms of intelligent demand forecasting. |
| doi_str_mv | 10.1109/ACCESS.2020.3003790 |
| format | Article |
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Business intelligence plays a pivotal role in an inevitable decision support system that enables the enterprise to perform analysis on data and throughout the process of business. Machine learning predicts the forecasting of future demands of the enterprises. Demand forecasting is one of the main decision-making tasks of enterprise. For demand forecasting first raw sales data is collected from the market, then according to data, the future sale/product demands are forecasted. This prediction is based on collected data that compiles through different sources. The machine learning engine executes data from different modules and determines the weekly, monthly, and quarterly demands of goods/commodities. In demand forecasting, its perfect accuracy is non-compromising, the more accurate system model is more efficient. Furthermore, we test the efficiency by comparing the predicted data with actual data and determine the percentage error. Simulation results show that after applying the purposed solution on real-time organization data, we get up to 92.38 % accuracies for the store in terms of intelligent demand forecasting.</description><identifier>ISSN: 2169-3536</identifier><identifier>EISSN: 2169-3536</identifier><identifier>DOI: 10.1109/ACCESS.2020.3003790</identifier><identifier>CODEN: IAECCG</identifier><language>eng</language><publisher>Piscataway: IEEE</publisher><subject>AWS sage maker ; Business ; Business intelligence ; Business machines ; Data collection ; Data models ; Decision analysis ; Decision support systems ; Demand ; Demand forecasting ; Economic forecasting ; Forecasting ; Information management ; Intelligence (information) ; Machine learning ; Mathematical models ; prediction ; Predictive models ; sale forecasting ; Training</subject><ispartof>IEEE access, 2020, Vol.8, p.116013-116023</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. 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| subjects | AWS sage maker Business Business intelligence Business machines Data collection Data models Decision analysis Decision support systems Demand Demand forecasting Economic forecasting Forecasting Information management Intelligence (information) Machine learning Mathematical models prediction Predictive models sale forecasting Training |
| title | Effective Demand Forecasting Model Using Business Intelligence Empowered With Machine Learning |
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