Excel
Also known as: Microsoft Excel, spreadsheet, XLSX, xls
Microsoft Excel is a spreadsheet application where data lives in a grid of rows and columns.
You can use it for simple lists, budgets, and calculations, or for complex financial models, pivot tables, and automated workflows. Excel is the default tool for business data analysis in most organizations and is widely expected as a core professional skill.
Excel, explained at three levels
At home
Excel is like a giant digital table where you can enter numbers, dates, or text in cells, and then do math on them automatically. If you track your monthly spending in column B, you can add a formula like =SUM(B2:B13) to add them all up. Excel does the math for you so you don't have to use a calculator.
At work
In most office jobs, Excel is the go-to tool for anything involving data -- expense reports, scheduling, tracking inventory, or summarizing survey results. Even if you never build a complex formula, being able to sort, filter, and format a table of data is a baseline expectation in most business roles.
At home
Intermediate Excel skills include VLOOKUP or XLOOKUP (finding data across sheets), pivot tables (summarizing large data sets without writing formulas), and conditional formatting (highlighting cells based on their value). These tools turn a raw list of transactions into a clear monthly summary with a few clicks.
At work
Business analysts use Excel for financial modeling, scenario analysis, and management reporting. Power Query lets you pull data from databases or web sources, clean it, and refresh it with one click. Pivot tables let you slice data by region, product, or time period without any coding. Charts and dashboards built in Excel are still the standard deliverable for many finance and operations teams.
At home
Advanced users leverage dynamic arrays (FILTER, SORT, UNIQUE, SEQUENCE) to build spreadsheets that update automatically as data changes. Excel's integration with Python (as of 2023) allows running pandas and matplotlib code directly in a cell. For personal finance modelling, named ranges, data validation, and linked workbooks can turn Excel into a sophisticated personal planning tool.
At work
At an enterprise level, Excel workbooks become systems of record with VBA macros, custom ribbon add-ins, and connections to SQL databases or ERP systems via Power Query or ODBC. Excel Services and Excel Online allow browser-based access to workbooks stored in SharePoint. Complex Excel models carry operational risk -- version control, auditability, and single-point-of-failure concerns push organizations toward Power BI or dedicated financial planning tools for critical reporting.
Real-world examples
At home
Carlos tracked his freelance income in Excel, with one column for client name, one for invoice amount, and one for payment date. He used a SUM formula at the bottom to see his total monthly earnings and a pivot table to see which client paid the most.
At work
Lena, a financial analyst, built a monthly P&L model in Excel with input assumptions in one tab and calculated results in another. When sales targets changed, she updated two cells and the entire model recalculated instantly, giving her updated forecasts to share with the CFO.
How it compares
| feature | Excel | Google Sheets | Power BI |
|---|---|---|---|
| Primary use | Spreadsheets, financial models | Collaborative spreadsheets | Business intelligence dashboards |
| Collaboration | Co-authoring in Microsoft 365 | Real-time browser collaboration | Published reports, not editing |
| Data limits | ~1 million rows | 10 million cells | Millions of rows (in-memory) |
| Coding integration | VBA, Python (2023) | Apps Script (JavaScript) | DAX, Python, R |
| Best for | Complex models, offline use | Simple shared tracking | Interactive dashboards |
Excel is the deepest tool for complex financial modelling and offline use. Google Sheets is simpler and better for quick team collaboration in a browser. Power BI is the right choice when you need interactive dashboards that non-analysts can explore without touching the underlying data.
For analysts
When assessing Excel use in a business, distinguish between light Excel (lists and basic formulas) and heavy Excel (financial models with macros and database connections). Heavy Excel workbooks are often unofficial systems of record and can be fragile -- a migration project may reveal undocumented business logic living only in a spreadsheet.
History & origin
Microsoft Excel launched in 1985 for the Macintosh, beating Lotus 1-2-3 on ease of use and graphics. The Windows version arrived in 1987. By the mid-1990s, Excel had displaced Lotus 1-2-3 as the dominant spreadsheet. Over the decades, Microsoft added pivot tables (1994), conditional formatting, Power Query (2013), and dynamic arrays (2018). Today Excel handles files with up to 1,048,576 rows and integrates with Power BI, Python (introduced in 2023), and Microsoft 365 cloud services.