Titlebook: Data Science and Analytics for SMEs; Consulting, Tools, P Afolabi Ibukun Tolulope Book 2022 Afolabi Ibukun Tolulope 2022 Data Science.Busin

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https://doi.org/10.1007/978-3-319-32653-5We then give a detailed explanation of the process involved in business analytics in the form of the business analytics journey. In this journey, we explain what it takes from start to finish to carry out an analytics project in the business world, focusing on small business consulting, even though

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Springer Proceedings in Complexitylain the types of business analytics consulting that exist and then narrow them down to how to navigate the world of business analytics consulting for small businesses. In this chapter, we will look at how to manage a typical analytics project and measure the success of analytics projects. In conclu

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Comparison, Diversity and Complexitywithin or outside the business. We will look at the proposal and initial stages of analysis that gives direction to the analytics project. Then we look at the details involved in the pre-engagement, engagement, and post-engagement phases. It is important to know that the stages are presented in a ty

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Africa: Globalisation and the Ethicalwill help to use descriptive analytics tools to understand your business and make recommendations that can improve your business profits. For small businesses, descriptive analytics helps SMEs to make sense of available data to monitor business indicators at a glance, help SME owners observe sales t

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Africa: Globalisation and the Ethicale techniques is to use them in solving a business problem. The business problem to be addressed is the sales prediction problem which is common in the retail business. The chapter first explains the fundamental concept of prediction techniques; next, we look at how such techniques are evaluated. Aft

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Mark Swilling,Pierre Roux,Amélie Guyotain. In doing this, we will use the third business problem centered on customer loyalty using neural networks, classification trees, and random forest algorithms. In solving this problem, we are particular about how to get and retain more customers for our small business. We will also introduce some

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Tanya de Villiers-Botha,Paul Cilliers a type of unsupervised learning approach. We will then pick one clustering technique which is the k-means clustering. Using the fourth practical business problem, we will explain how we can use the k-means clustering technique to solve a real business problem. Next, we will explain the association