Book

Description

Business Intelligence and Data Analytics: A Comprehensive Guide is published in two companion volumes. Volume I presents the complete text in English; Volume II presents the Chinese edition. Both volumes share an identical thirteen-chapter structure and may be used independently or as an integrated set. Anchored to the CRISP-DM lifecycle, the thirteen chapters progress from data-driven strategy, probability, statistical inference, and optimization to data cleaning, exploratory analysis, feature engineering, and visualization. Core modeling covers regression, classification, unsupervised learning, time-series forecasting, and deep learning, closing with model deployment, interpretability, and MLOps. Each chapter integrates Python-based labs and explicit discussion of algorithmic ethics and bias. The English edition is designed for bilingual programs and English-medium instruction; the Chinese edition serves native-speaking students and practitioners seeking a rigorous, end-to-end analytics pipeline. 《商业智能与数据分析：综合指南》分卷独立出版。第一卷为英文版（Business Intelligence and Data Analytics: A Comprehensive Guide, Volume I），第二卷为中文版。两卷共享相同的十三章结构，既可独立使用，亦可配套研读。 全书以 CRISP-DM 跨行业数据挖掘标准流程为主线，从数据驱动战略、概率论、统计推断与最优化基础，延伸至数据清洗、探索性数据分析、特征工程与可视化原理。核心建模涵盖回归、分类、无监督学习、时间序列预测与深度学习架构，末章收束于模型部署、可解释性与 MLOps 治理。每章配备 Python 动手实践，并贯穿算法伦理与偏见治理的讨论。英文版服务于双语课程与全英文授课需求；中文版面向中文读者，提供严谨、端到端的现代数据分析方法论训练。