Many spreadsheet requests begin with “Can you take a look at this?” The workbook may contain useful evidence, but the real question, field meanings, inconsistent labels, missing values, formulas, and decisions are scattered across rows and sheets. Finding a trustworthy answer is often harder than adding the numbers.

AI can inspect workbook structure, organize repeated checks, create cleaned columns and summaries, and explain changes without requiring you to memorize advanced Excel functions. It can also follow the wrong question quickly, overwrite source data, choose a convenient denominator, or turn a plausible calculation into an overconfident recommendation.

This Course teaches a reusable source-to-decision method. You take responsibility for a Course-supplied Q1 workshop workbook and prepare evidence for a manager deciding which two workshop types deserve a next-quarter scheduling discussion. All practice records and values are synthetic. AI helps with the repeated spreadsheet work; you decide the goal, approve treatments, test decisive numbers, interpret uncertainty, and leave the scheduling decision with the manager.

Across six Lessons, you will:

• frame the decision and protect the original workbook before analysis begins;
• inspect one-row meaning, field rules, repeated IDs, valid blanks, and unsupported values;
• build cleaned evidence without erasing raw values or guessing repairs;
• compare workshop types through capacity use, net session contribution, and response-weighted ratings;
• reconcile counts, totals, the amounts being added, and the totals they are divided by back to eligible rows;
• write a conditional recommendation that separates results, interpretation, limits, and next actions; and
• audit formulas, source preservation, rendering, and the exported workbook before handoff.

The final result is an editable eight-sheet .xlsx workbook with unchanged sources, cleaned data, a comparison, visible checks, an issue log, and a decision summary. It is marked ready for manager review. It is not an approved schedule, a profit report, a forecast, or a claim that every source problem has been corrected.

You do not need to be a data analyst, write code, build PivotTables, or reproduce long formulas. You should already understand ordinary rows and columns and be able to open an Excel workbook. The method transfers to expenses, registrations, surveys, inventories, trackers, and other everyday tables even when you use a different spreadsheet or AI tool.