Artificial Intelligence for Business Analytics

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Methods of artificial intelligence (AI) have transitioned from scientific discussions to everyday applications. As digitalization increases, the volume of data generated is also rising, driven by digital measurement systems and the Internet of Things. Companies can no longer rely solely on business intelligence (BI) and historical data; they must adopt business analytics, incorporating predictive analyses and automated decision-making to remain competitive. The challenge of leveraging vast amounts of data highlights the importance of AI in data analysis. This book offers a clear introduction to essential AI methods for business analytics, presenting machine learning concepts and key algorithms within a business analytics technology framework, along with application scenarios across various industries. It also introduces the Business Analytics Model for Artificial Intelligence, a reference model for structuring BA and AI projects within organizations. This work is a translation of the original German edition by Felix Weber, published in 2020, and has been translated using AI, followed by a thorough human revision to enhance content clarity. Springer Nature is committed to advancing book production tools and related technologies to support authors.