Название: AI Meets BI: Artificial Intelligence and Business Intelligence Автор: Lakshman Bulusu, Rosendo Abellera
Издательство: CRC Press / Auerbach Publications
Год: 2020
Страниц: 241
Язык: английский
Формат: pdf (true)
Размер: 11.3 MB
This book focuses on the primary aspect of "AI meets BI" and details the intersection of AI, data science, machine learning, deep learning, and cognitive computing and how these technologies can assist and/or automate BI and decision making, resulting in more informed business insights. It stands out as the first publication to address the integration of artificial intelligence tools and technologies from the multitude of such tools and technologies available today to boost and enhance business intelligence. It covers various AI-powered analytics for BI-enabled decision making. Specifically, it discusses four industry use cases and their implementation, using AI-enabled machine learning and deep learning techniques along with their integration into enterprise BI platforms, by making use of the abovementioned technologies. It also discusses how all types of data, including Big Data, can be scaled to enter prise level and thereby enhance customer experience. Details are discussed from a business perspective and the AI-way of implementation.
With the emergence of Artificial Intelligence (AI) in the business world, a new era of Business Intelligence (BI) has been ushered in to create real-world business solutions using analytics. BI developers and practitioners now have tools and technologies to create systems and solutions to guide effective decision making. Decisions can be made on the basis of more reliable and accurate information and intelligence, which can lead to valuable, actionable insights for business. Previously, BI professionals were stymied by bad or incomplete data, poorly architected solutions, or even just outright incapable systems or resources. With the advent of AI, BI has new possibilities for effectiveness. This is a long-awaited phase for practitioners and developers and, moreover, for executives and leaders relying on knowledgeable and intelligent decision making for their organizations.
Beginning with an outline of the traditional methods for implementing BI in the enterprise and how BI has evolved into using self-service analytics, data discovery, and most recently AI, AI Meets BI first lays out the three typical architectures of the first, second, and third generations of BI. It then takes an in-depth look at various types of analytics and highlights how each of these can be implemented using AI-enabled algorithms and deep learning models.
The intended audience for this book includes business and data analysts who need to interpret the output of AI-powered BI systems from a business perspective; data scientists; data engineers; AI and BI practitioners, designers, programmers, and technical/project managers involved in AI/BI solution implementations; academia and research scientists involved in teaching/training of AI/BI models; and, last but not least, teachers and students of data science/AI/BI courses at the graduate level and/or in career-based learning courses.
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