Ai-Powered Business Intelligence: Improving Forecasts and Decision Making with Machine Learning

Use business intelligence to power corporate growth, increase efficiency, and improve corporate decision-making. With this practical book, you'll explore the most relevant AI use cases for BI, including improved forecasting, automated classification, and AI-powered recommendations. And you'll learn how to draw insights from unstructured data sources like text, image, and voice audio files.

Author Tobias Zwingmann, senior data scientist and cofounder of Germany-based AI startup RAPYD.AI, helps BI, business, and data analysts understand high-impact areas of predictive and prescriptive analytics. You'll learn how to leverage popular AI-as-a-service and AutoML platforms to ship enterprise-grade proof of concepts without the help of software engineers or data scientists.

• Learn how AI can generate business impact in BI environments
• Use AutoML for automated classification and improved forecasting
• Implement recommendation services to support decision-making
• Draw insights from text data at scale with NLP services
• Extract information from documents and images with computer vision services
• Build interactive user frontends for AI-powered dashboard prototypes
• Implement an end-to-end case study for building an AI-powered customer analytics dashboard

使用商業智能來推動企業增長、提高效率和改善企業決策。這本實用書籍將探討商業智能中最相關的人工智能應用案例，包括改進預測、自動分類和基於人工智能的推薦。您還將學習如何從非結構化數據源（如文本、圖像和語音音頻文件）中獲取洞察。

作者Tobias Zwingmann是德國AI初創公司RAPYD.AI的高級數據科學家和共同創始人，幫助商業智能、業務和數據分析師了解預測性和指導性分析的高影響領域。您將學習如何利用流行的AI即服務和AutoML平台，在沒有軟件工程師或數據科學家的幫助下交付企業級概念驗證。

- 學習AI如何在商業智能環境中產生業務影響
- 使用AutoML進行自動分類和改進預測
- 實施推薦服務以支持決策
- 使用NLP服務大規模從文本數據中獲取洞察
- 使用計算機視覺服務從文檔和圖像中提取信息
- 為基於人工智能的儀表板原型構建交互式用戶界面
- 實施一個端到端的案例研究，構建一個基於人工智能的客戶分析儀表板