Snowflake：2025湖仓分析与人工智能必备指南：为AI新时代设计企业分析体系（英文版）（14页）.pdf

1、LAKEHOUSE ANALYTICS AND AIDesigning enterprise analytics for the new era of AIESSENTIAL GUIDETABLE OF CONTENTSThe Imperative of Lakehouse Analytics in the Age of AI .3The Open Lakehouse:Storage,Catalog and Compute .4Architecting a Resilient Lakehouse Analytics and AI Practice .6Common Pitfalls of Tr

2、aditional Lakehouse Solutions .8Snowflake for Lakehouse Analytics and AI .10Charting Your Course:A Practical Transition Strategy .12Conclusion:From Data to Impact .13Table of Contents|2 ESSENTIAL GUIDE TO LAKEHOUSE ANALYTICS AND AITHE IMPERATIVE OF LAKEHOUSE ANALYTICS IN THE AGE OF AIFor data leader

3、s responsible for shaping their organizations future architects,CIOs and CDOs the strategic challenge is no longer just about managing data.Its about unifying a vast and varied data estate to power todays business intelligence and AI-driven innovation.The answer for many forward-thinking organizatio

4、ns with an in-house data engineering team is the open lakehouse.This modern architectural approach promises to deliver the best of two worlds:the performance and governance of a traditional data warehouse combined with the flexibility and scale of a data lake.A lakehouse architecture untangles stora

5、ge,catalog and compute,providing the flexibility to choose the right tools for each team.A lakehouse architecture untangles storage,catalog and compute,providing the flexibility to choose the right tools for each team.The emergence of Apache Iceberg as the leading vendor-neutral and interoperable op

6、en table format has accelerated this trend by making it easier to bring tools to your data,rather than data to your tools.The result is greater data democratization by empowering organizations to rapidly adopt new tools,drive faster innovation,and scale analytics and AI initiatives all via a single