Data Layer Architecture

Dashboards practice bundle

Download dashboards-practice.zip and extract it before opening the workbooks.

• dashboard-starter.xlsx: dashboard canvas and a CALC sheet with financial-year and region selectors. Import the CSVs into your own RAW sheets, create named tables, and build the calculations and charts during the lessons.
• dashboard-reference.xlsx: checked summary tables for all three projects. These are static answer tables; build your own PivotTables, formulas, charts and filter connections.
• sales/: 50,000 orders covering FY2024-25 and FY2025-26, plus 48 region/month targets for FY2025-26 only.
• finance/: monthly actual/budget P&L, line classifications and annual balance-sheet inputs.
• marketing/: monthly channel metrics, separate campaign totals and cohort retention rates.
• solutions-en.md and solutions-hi.md: worked guidance for all 22 lessons.
• answer-key.json and audit_dashboards.py: numerical references and an optional Python 3 audit using only the standard library.

Money is in rupees; divide by 100,000 to display lakh. FY runs April–March. Import ISO dates as dates, identifiers as text and monetary fields as numbers. The modern formula lessons use Microsoft 365 functions.

Show unavailable targets as blank for FY2024-25. Label all-region sales heatmaps separately from region-filtered panels. Finance cash movements and balance-sheet ratios are annual; keep these separate from monthly P&L filters. Marketing cohorts have no Channel field and campaigns have no Month field, so label their independent scope. Treat all data as synthetic practice material.