商业数据分析：AI-ML-PBI-SQL-R（真正的EPUB）

English | 2024 | ISBN: 9781003336099 | 349 pages | True EPUB | 8.59 MB

We are drowning in data but are starved for knowledge. Data Analytics is the discipline of extracting actionable insights by structuring, processing, analysing and visualising data using methods and software tools. Hence, we gain knowledge by understanding the data. A roadmap to achieve this is encapsulated in the knowledge discovery in databases (KDD) process. Databases help us store data in a structured way. The structure query language (SQL) allows us to gain first insights about business opportunities. Visualising the data using business intelligence tools and data science languages deepens our understanding of the key performance indicators and business characteristics. This can be used to create relevant classification and prediction models; for instance, to provide customers with the appropriate products or predict the eruption time of geysers. Machine learning algorithms help us in this endeavour. Moreover, we can create new classes using unsupervised learning methods, which can be used to define new market segments or group customers with similar characteristics. Finally, artificial intelligence allows us to reason under uncertainty and find optimal solutions for business challenges. All these topics are covered in this book with a hands-on process, which means we use numerous examples to introduce the concepts and several software tools to assist us. Several interactive exercises support us in deepening the understanding and keep us engaged with the material.

This book is appropriate for master students but can also be used for undergraduate students. Practitioners will also benefit from the readily available tools. The material was especially designed for Business Analytics degrees with a focus on Data Science and can also be used for machine learning or artificial intelligence classes. This entry-level book is ideally suited for a wide range of disciplines wishing to gain actionable data insights in a practical manner.

英文| 2024 |国际标准图书编号：978100336099 | 349页|真正的EPUB | 8.59 MB 我们淹没在数据中，却渴望知识。数据分析是一门通过使用方法和软件工具对数据进行结构化、处理、分析和可视化来提取可操作见解的学科。因此，我们通过理解数据来获得知识。实现这一目标的路线图被封装在数据库中的知识发现（KDD）过程中。数据库帮助我们以结构化的方式存储数据。结构查询语言（SQL）使我们能够初步了解商机。使用商业智能工具和数据科学语言对数据进行可视化，加深了我们对关键绩效指标和业务特征的理解。这可用于创建相关的分类和预测模型；例如，为客户提供合适的产品或预测间歇泉的喷发时间。机器学习算法在这方面为我们提供了帮助。此外，我们可以使用无监督学习方法创建新的类，这些类可用于定义新的细分市场或将具有相似特征的客户分组。最后，人工智能使我们能够在不确定性下进行推理，并为业务挑战找到最佳解决方案。本书通过实践过程涵盖了所有这些主题，这意味着我们使用了许多例子来介绍概念，并使用了几个软件工具来帮助我们。几个互动练习帮助我们加深理解，让我们与材料保持联系。 这本书适合硕士研究生阅读，也适合本科生阅读。从业者也将受益于现成的工具。该材料是专门为商业分析学位设计的，重点是数据科学，也可用于机器学习或人工智能课程。这本入门级的书非常适合希望以实用的方式获得可操作数据见解的广泛学科。

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