Common Excel analysis formulas
Total sales by region:   =SUMIFS(Sales[Amount], Sales[Region], "North")
Lookup a product price:  =XLOOKUP(A2, Products[ID], Products[Price], "Not found")
Growth vs last month:    =IFERROR((C3-C2)/C2, 0)
Rank sales reps:         =RANK.EQ(D2, $D$2:$D$20, 0)

Total Sales = SUM ( Sales[Amount] )

Sales LY =
CALCULATE ( [Total Sales], SAMEPERIODLASTYEAR ( 'Date'[Date] ) )

Sales Growth % = DIVIDE ( [Total Sales] - [Sales LY], [Sales LY] )
-- Requires a marked date table related to Sales

let
    Source = Excel.Workbook(File.Contents("C:\data\sales.xlsx"), null, true),
    Sales = Source{[Item = "Sales", Kind = "Sheet"]}[Data],
    Promoted = Table.PromoteHeaders(Sales, [PromoteAllScalars = true]),
    Typed = Table.TransformColumnTypes(Promoted, {{"Date", type date}, {"Amount", type number}}),
    Trimmed = Table.TransformColumns(Typed, {{"Region", Text.Trim, type text}})
in
    Trimmed
// The same M code works in Excel's Power Query and in Power BI

Star schema for a sales report
Fact table:  Sales (DateKey, ProductKey, StoreKey, Amount, Quantity)
Dimensions:  Date (DateKey, Month, Year)
             Product (ProductKey, Category, Brand)
             Store (StoreKey, City, Region)
Relationships: one-to-many from each dimension to Sales
This structure makes Power BI measures simple and fast.

Choose the tool
One-time question, small data          → Excel
Financial model, scenarios              → Excel
Report that refreshes every week        → Power BI
Many viewers with different filters     → Power BI
Data from several tables/sources        → Power BI (or Excel Data Model)
Need to share a quick table by email    → Excel

Excel pivot table in five steps
1. Format data as a table (Ctrl+T)
2. Insert → PivotTable
3. Rows: Region; Columns: Month; Values: Sum of Amount
4. Add a slicer for Product Category
5. Insert a PivotChart for a quick visual

Recommended order
1. Excel basics: formulas, sorting, filtering, formatting
2. Excel analysis: SUMIFS, XLOOKUP, pivot tables, charts
3. Power Query in Excel: cleaning and combining data
4. Power BI: loading data, relationships, star schema
5. DAX basics: SUM, CALCULATE, DIVIDE, time intelligence
6. Dashboard design and publishing

Practice project with both tools
Data: public retail sales dataset
Excel: clean with Power Query, pivot by region and month, quick insights
Power BI: build star schema, measures for sales and growth, 2-page dashboard
Write-up: when you used each tool and why

Skills checklist
Excel: ☐ SUMIFS ☐ XLOOKUP ☐ pivots ☐ charts ☐ Power Query
Power BI: ☐ relationships ☐ star schema ☐ measures ☐ CALCULATE ☐ slicers ☐ publishing