CIS 2270 A Framework for Humanizing Data Analysis

The session focuses on humanizing data analysis for higher education business and data analysts by shifting from technical perfection to impactful conversations with stakeholders. It guides participants through common traps analysts face—such as prioritizing tools over real problems, failing to tailor information for different audiences, and working in isolation—and replaces these with collaborative, audience-centered approaches.​

• The session opens by questioning why perfect data work sometimes fails to influence decisions and introduces the theme that conversations, not just better tools, are the key to impact.
• The session organizes its content around five "traps," including starting with the tool instead of the problem, using one-size-fits-all explanations, focusing too much on technical details, neglecting to define the root issue, and working alone.
• Engagement elements like polls, breakout activities, real scenarios, and live Q&A drive home the importance of audience understanding, collaborative problem-solving, and making data analysis a human-centered discipline.

Note: the focus of this course on mindset rather than technical expertise. The intended audience are professionals (from early to mid-career) who are involved in some form of business or data analysis and are seeking ways to rethink their data challenges using a human-first approach.