In today's volatile business landscape, professionals face critical decision-making dilemmas—relying on vague intuition when making key business choices or drowning in data without extracting actionable insights. Teams often spiral into trial-and-error cycles when KPIs decline; when questioned by leadership, they lack data-backed justification; when challenged on solutions, "industry norms" replace evidence-based arguments. Compounding this, AI-empowered colleagues solve problems at speed while others remain trapped in manual data processes. This session will preliminarily solve those problem, help students build a data analysis empowered decision-making mindset through scientific and effective data analysis mindset as well as AI data-analysis tools.

在瞬息万变的商业环境中，许多职场人深陷决策困境——面对关键业务选择时，要么依赖模糊的经验直觉，要么被海量数据淹没却无法提炼有效结论。当KPI下滑时，团队常陷入反复试错的恶性循环；当老板追问决策依据时，只能给出缺乏数据支撑的苍白解释；当汇报被挑战方案合理性时，只能以"行业惯例"搪塞却拿不出有说服力的证据。更令人焦虑的是，掌握AI数据分析工具的人已能够迅速分析解决问题，而自己仍困在手工处理数据的低效流程中。本次活动将解决以上问题，通过分享科学有效的数据分析思维方式和AI数据分析工具，帮助参与者轻松建立数据导向的职场决策思维。

Outline/课程大纲

Interaction Case : Data analysis mindset

• Reflection: How to build a data analysis empowered decision-making mindset
• Business case study for business performance improvement

Clarify the problem itself

Select the data analysis tools and draw statistical conclusion

• Scientific data collection
• Effectively present data collection result
• Key statistics
• Key performance indicators
• Visualization

Exercise: practice with AI tools for data presentation

• Find out the root causes through AI empowered data analysis
• Data analysis foundation
• Hypothesis test
• Correlation
• Regression
• Above-montioned data analysis using AI tools

Exercise: data analysis practice with the simulation case data (using AI tools)

Find practical solutions

• Generate potential solutions: structured brainstorming
• Select the optimal solutions: prioritization tools
• Summary and recap

互动案例：正确的数据思维

思考：如何建立基于数据分析的科学决策思维

• 某业务表现提升模拟情景的背景介绍（初始状态）
• 明确问题本身
• 选择数据分析工具并得出统计学结论

科学收集数据

• 定义数据收集方法
• 检验数据收集方法的可靠性
• 理解抽样原理
• 选择抽样方法

用AI工具有效呈现结果

• 关键统计量
• 流程表现指标
• 可视化

练习：用AI工具有效呈现结果的实操练习

• 用AI工具通过数据分析工具识别根本原因
• 数据分析基本原理
• 假设检验
• 相关分析
• 回归分析
• 以上数据分析在AI工具中的实现

练习：基于模拟情景中数据的定量分析工具实操练习（需使用AI工具）

• 找到现实中的方案
• 生成潜在方案：结构化头脑风暴
• 筛选最优方案：优先级排序工具

总结与回顾

Date

20 Oct, 2026, Tuesday

Time

1:30 PM - 5:30 PM (Beijing Time)

Venue

An email will be sent with instructions to join online training via Microsoft Teams Meeting platform 2 days prior to the event.

线上培训链接将在培训前两天通过邮件方式通知报名学员。

Price

1000 RMB: Early Bird (Until Aug 28)

1300 RMB: Member

1600 RMB: Non-Member

Language

In Chinese 中文讲解

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