Data is everywhere, but useful insight is harder to find.
Many professionals have access to dashboards, spreadsheets, reports and AI tools, yet still struggle to turn information into clear recommendations. The challenge is no longer just collecting data. It is knowing which questions to ask, which metrics matter, how to interpret patterns responsibly and how to communicate findings in a way that supports better decisions.
This webinar introduced the practical skills learners will build through the University of Minnesota’s Data Analytics Certificate. The session explored how business intelligence reporting and decision-support analytics can help professionals move beyond static reports toward clearer, more actionable insights. Participants considered how generative AI is changing the analytics workflow, including how it can support brainstorming, data quality checks, KPI development, dashboard storytelling and executive communication when used responsibly.
Through this session, participants learned to:
- recognize the difference between having data and using data to support decisions.
- identify the kinds of business questions that can be supported through reporting, dashboards and applied analytics.
- describe how KPIs, data visualization and executive summaries can help translate analysis into action.
- consider responsible ways generative AI can support but not replace human judgment in analytics work.
Dr. Gina Debogovich is a digital strategist, analytics leader and educator with experience leading social, digital and data-informed decision-making initiatives for major organizations including Amazon, Best Buy, AT&T and UnitedHealth Group. Her work has included executive reporting, dashboard development, KPI strategy, marketing and social media analytics, AI adoption and translating complex data into practical insights for business leaders.
Key Takeaways
Clarify the Business Question First: The primary challenge in analytics isn't collecting more data, but identifying which questions to ask. Reporting issues usually stem from vague requests. Asking clarifying questions upfront ensures you build reports that directly support decision-making.
Dashboards are Formats, Not Outcomes: Dashboards and charts exist to focus attention on the information needed to make decisions, not just to display data.
Select the Right Visualizations: Match your chart type directly to the question you are answering to make insights easily recognizable:
- Bar Chart: Categorical comparisons and rankings.
- Line Chart: Trends and changes over time.
- Scatter Plot: Relationships between two variables.
- Pie Chart: Showing how a whole is divided into a few meaningful parts.
- Table / KPI Card: Displaying exact values or a single critical headline number.
Craft Action-Oriented Summaries: An executive summary should connect data points into a cohesive narrative that answers three core questions: What happened? Why does it matter? What should we do next?
Responsible AI Integration: Generative AI tools (e.g., ChatGPT, Gemini) can accelerate routine tasks, brainstorm visual concepts, check data quality, and draft initial summaries. However, humans must retain accountability, validate data accuracy, and apply contextual judgment.