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Data Analytics

This week we were asked to discuss the introduction section of the final paper and give as well as receive feedback. My introduction is as follows:

Data analytics, reduce costs, enhance logistic timelines, and engage with customers. One way that businesses use the data they obtain is to forecast future sales. Forecasting sales can be made using a company’s historical information. “Both analytics and data are increasingly central to decision-making in modern organizations,” (Power et al., 2018). One problem that businesses encounter when they do not adequately forecast sales, is not providing enough inventory to meet the customer’s demand. This can be problematic, especially during the holiday season when sales increase. Businesses need to provide enough inventory for customers because if they do not, it could create animosity and prevent them from returning. If a customer is not satisfied, they may not return for a long period. “Time absence plays an important role in relationship revival,” between a company and their customers which can affect their general willingness to return (Pick et. al., 2016). The data that will be collected throughout this project, will help guide the company to determine which departments will need to increase their stock to meet demand during holiday seasons. There will be many key factors that this paper will discuss which include a literature review, the data that will be used, methods, the three stages of analysis, and the results. The goal is to provide the information in a way that both analysts and company managers can understand to improve their performance and gain a greater understanding of their overall sale