Most businesses have more data than time to analyze it. AI features now built into spreadsheets and dashboards let workers ask questions in plain language, clean messy data faster, spot trends and outliers, and write the story behind the numbers. They also make it easy to produce a confident chart that is wrong. This instructor-led course teaches workers to use AI-assisted analytics accurately on their own reports. Trainees practice with Copilot in Excel, Power BI Copilot and Q&A, Tableau AI and Tableau Pulse, and data analysis in ChatGPT or Gemini, using fictional Massachusetts business datasets such as a manufacturer's scrap log, a clinic's scheduling data, an inn's bookings, and an insurance agency's renewal list. Each session follows the analytics workflow: prepare and clean data, explore and question it, visualize it, explain it, and share it with the right controls. Every AI result is checked with a manual calculation or a second method before it goes on a report. Trainees learn how data models, permissions, and refresh affect what AI can see. Each trainee builds a small AI-assisted dashboard or report and a written data story for a real decision in their role, presented to the cohort. Designed for analysts, coordinators, and managers who build or use reports.
What you will be able to do
By the end of the course, trainees will be able to:
- Clean and prepare a messy dataset with AI assistance and document every transformation.
- Ask plain-language questions in Excel, Power BI, or Tableau and verify at least three answers manually.
- Build a dashboard or report with at least four visuals chosen to fit the question.
- Write an AI-assisted narrative summary of findings that contains no unsupported claims.
- Apply sharing permissions and data sensitivity labels correctly in the lab environment.
Who this course is for
Business, operations, and financial analysts; Sales and marketing analysts; Office and practice managers; Production and quality supervisors; Revenue cycle and healthcare operations staff; Bookkeepers and accountants
Before you start
Intermediate spreadsheet skills (pivot tables or willingness to learn them in session 1). Access to the employer's BI tool or acceptance of sandbox delivery.
Hands-on activities
- Data cleanup lab: fictional Bayside Precision Parts scrap log with duplicates, typos, and mixed date formats.
- Question-and-verify lab: ten plain-language questions; trainees verify three with formulas or pivots.
- Visual choice clinic: fix five misleading AI-generated charts.
- Narrative lab: AI-drafted data story, then fact-check every sentence against the data.
- Sharing and permissions lab in sandbox workspace.
- Capstone dashboard and data story presentation.
How your learning is measured
- Attendance at all five sessions.
- Five lab deliverables scored on a 3-level rubric.
- Verification log: three AI answers checked manually per lab.
- Capstone dashboard and data story scored against rubric and presented.
