- About This Article
- What Is This?
- Where Does It Fit Within Google?
- Who Uses It?
- What Can It Do?
- How Is It Used in Practice?
- Usage Requirements
- Use Cases for Administrative Staff
- What IT Administrators Should Focus On
- What Developers Should Focus On
- Trying It Out with Commands and Code
- Hands-on with Papanda: Reading Sheets Cells and Comparing with Excel
- What Are the Closest Microsoft Products?
- Security Considerations
- Common Misconceptions
- Current Name and Availability
- Conclusion
- Official Information and Primary Sources
- What Kind of Service Is It Ultimately?
About This Article
This article was generated using a generative AI-powered automation workflow. "What is Google Sheets? Differences from Excel and Business Automation" is structured to help beginners grasp the big picture, covering its role, use cases, related services, and practical considerations.
Information Verification Date: 2026-09-19
About This Article
Google Sheets is examined not only as a spreadsheet application, but also from the perspectives of co-editing, BigQuery integration, and API automation.
Verification Status: Official Google primary sources verified as of 2026-09-18. Specifications, pricing, and availability will be re-confirmed prior to publication.
What Is This?
Google Sheets is Google's cloud spreadsheet service. It provides real-time co-editing, version history, Excel file editing, external data integration, Connected Sheets, and automation through Apps Script and the Sheets API.
Where Does It Fit Within Google?
flowchart LR U[利用者] --> S[Google Sheets] S --> C[共同編集] S --> X[Excelファイル] S --> B[BigQuery / Looker] DEV[Apps Script / Sheets API] --> S
It is a spreadsheet product within Google Workspace, positioned at the intersection of business data input/sharing and automation.
Who Uses It?
| Readers | Relevant Points |
|---|---|
| General Users | Household budgets, lists, and simple aggregations |
| Administrative & Business Users | Co-editing, data aggregation, progress tracking, and form preparation |
| IT Administrators | Sharing, external integrations, and add-on management |
| Developers | Apps Script / Sheets API |
What Can It Do?
Real-time co-editing
Direct editing of Excel files
Functions, pivot tables, and charts
Connected Sheets
Gemini features
Apps Script / API
How Is It Used in Practice?
Simultaneous input by multiple users
Analyzing BigQuery data within Sheets
Writing data daily via API
Migrating from Excel to cloud co-editing
Usage Requirements
| Item | Details |
|---|---|
| Free / Paid | Available with a Google account. Advanced features vary by Workspace plan |
| Google Account | Required for creation and editing |
| Google Cloud Project | Not required for general use. Required for API development |
| API | Google Sheets API available |
| Primary Authentication | OAuth 2.0 / Service Account, etc. |
| Windows / Ubuntu | Web-centric. Compatible with both Windows and Ubuntu |
Use Cases for Administrative Staff
For administrative staff, the ability for multiple people to edit the same file simultaneously is a major advantage. On the other hand, existing VBA macros and complex Excel add-ins cannot be migrated as-is, so functional differences should be identified before migration.
What IT Administrators Should Focus On
External sharing
Apps Script permissions
Add-on permissions
Data connection destinations
Copying and exporting outside the organization
What Developers Should Focus On
Retrieving and updating values via the Sheets API
Automating workflows within Workspace using Apps Script
Deciding to offload large-scale data to BigQuery
Trying It Out with Commands and Code
# 例: gspread等ではなく公式クライアントを使う場合も、 # 認証情報はコードへ直書きしない。 SPREADSHEET_ID = 'DUMMY_SPREADSHEET_ID' RANGE = 'Sheet1!A1:C10'
Hands-on with Papanda: Reading Sheets Cells and Comparing with Excel
Visible Output: Read the A1 range of a public sample sheet and display it in a tabular format in the terminal.The official Google Python quickstart allows you to retrieve cell values using a read-only scope. Start by using the official sample spreadsheet, and if the expected rows are displayed, you are successful.
A candidate Daily Code structure consists of three steps: (1) Sheets API to CSV, (2) formatting the CSV with PowerShell, and (3) reading the same CSV into Excel Power Query, visually comparing "API -> CSV -> Excel". If creating a VBA version, avoid embedding tokens in cells or the VBA source code by separating the authentication logic from the table processing logic.
What Are the Closest Microsoft Products?
Microsoft Excel is the direct comparison. While co-editing and cloud integration features are becoming more similar, the feature sets including VBA, Power Query, and others differ.
This is not a strict one-to-one correspondence. Because product design philosophies, permission models, pricing, and integration scopes differ, comparison articles should focus on specific use cases.
Security Considerations
Check sharing links for confidential data
Avoid over-sharing with Service Accounts
Verify the scopes requested by Apps Script
Common Misconceptions
Is Sheets fully compatible with Excel?
No. While basic spreadsheet functions are similar, differences exist in VBA, Power Query, detailed formatting, add-ins, and more.
Is Sheets suitable for large volumes of data?
Depending on the scale and analysis requirements, it may be better to separate data into BigQuery or a database.
Current Name and Availability
Google Sheets is currently available. Check your plan and environment for Gemini and Connected Sheets availability.
Conclusion
Google Sheets is a cloud spreadsheet powerful in co-editing, and serves as a gateway to business automation when including Apps Script, APIs, and BigQuery integration.
Official Information and Primary Sources
What Kind of Service Is It Ultimately?
"What is Google Sheets? Differences from Excel and Business Automation" is best understood not by just memorizing the name, but by grasping "who uses it, for what purpose, and which Google services it connects to." Start by reviewing official information and existing secure samples, test them on a small scale in a verification environment, and then expand to actual operations.
