Book 3 · Chapter 5: Dashboards and Trackers
This page picks the right chart for your data, with sample spreadsheets, dashboard brief templates, and a data-prep checklist.
This page assumes you've read the chapter. It hands you the tools, not the lessons.
You don't pick a chart type, you pick the question you're asking. Choose one and see the right chart, live, on sample data.
Bar chart
Bar charts compare categories. If the question is "which one is bigger?", a bar chart is your answer.
Sample data: monthly spending by category.
Three small, clean datasets so you can build the chapter's dashboards before wrangling your own data.
Project tracker data
18 projects with owner, status, start date, deadline, percent complete, and notes. Feeds Build 1 (the project tracker dashboard).
project-tracker.csv
Household budget data
Two months of clean transactions (date, description, amount) for Claude to categorize. Feeds Build 2 (the budget dashboard).
household-budget.csv
Sales pipeline data
14 deals with company, stage, value, expected close date, owner, and last activity. Feeds Build 3 (the pipeline dashboard).
sales-pipeline.csv
- Build 1: Project tracker dashboard
PURPOSE: A project tracker dashboard for my team. I manage 15-20 active projects and need to see status, deadlines, and risk at a glance. Just for me and my manager. LAYOUT: Summary cards across the top showing total projects, how many are on track, how many are at risk, and how many are overdue. Below that, a bar chart showing projects by status. Below that, a sortable table with all project details. ACTIONS: When I click a column header in the table, it sorts by that column. Add a dropdown filter for status (All, On Track, At Risk, Overdue) and one for project owner. When a deadline is within 7 days, highlight the row in yellow. When a deadline has passed and the project isn't complete, highlight it in red. DATA: Columns: Project Name, Owner, Status (On Track / At Risk / Overdue / Complete), Start Date, Deadline, Percent Complete, Notes. I'll upload a CSV with this data. STYLE: Professional and clean. This might be on screen during a meeting with my VP.
- Build 2: Household budget dashboard
PURPOSE: A personal budget dashboard to visualize my monthly spending. Just for me (and maybe my partner). I want to see where the money goes and whether I'm staying within budget. LAYOUT: Monthly spending summary at the top (total spent, budget remaining, biggest category). A bar chart showing spending by category. A line chart showing spending trend over the last six months. A table with all transactions, most recent first. ACTIONS: Let me filter by category using a dropdown. When I click a category in the bar chart, show only those transactions in the table below. If spending in any category exceeds my budget for that category, color the bar red. Let me toggle between monthly and weekly views. DATA: I'll upload my bank export CSV. Columns are Date, Description, Amount. I need Claude to categorize transactions: group food-delivery services and restaurant names under "Dining Out." Group the big online and grocery retailers under "Shopping." Group rent/mortgage, utilities, and insurance under "Housing." I'll specify other groupings as needed. STYLE: Clean and personal. Not corporate-looking. I want to enjoy opening this.
- Build 3: Pipeline dashboard (DATA section; the rest mirrors Build 1)
DATA: Connect to my Google Sheet called "Sales Pipeline." Columns are: Deal Name, Company, Stage (Lead / Qualified / Proposal / Negotiation / Closed Won / Closed Lost), Deal Value, Expected Close Date, Owner, Last Activity Date. Pull fresh data every time I open this dashboard.
Two quick passes before you upload save you a frustrating first build.
- 1Check your column headers. Claude reads your headers to understand what the data means. Rename any cryptic headers to plain English before you export.
- 2Remove the junk rows. Summary rows at the bottom ("Grand Total"), blank rows in the middle of your data, merged cells that made sense in Excel but confuse everything else.
- 3For bank or financial exports, watch for: date format inconsistencies, currency symbols stuck in amount columns, and negative amounts used for debits.