Glide Data Modeling

Key Concept: Column-Based Calculations

IMPORTANT: All calculations in Glide are built in the Data Editor by adding computed columns that build off one another. Unlike spreadsheets with cell formulas, Glide uses a column-based computation model.

To build complex calculations:

1. Create intermediate computed columns
2. Chain columns together (one column references another)
3. Build up to your final result step by step

Example: Calculate total with tax

1. Column: Subtotal (Math: Price * Quantity)
2. Column: Tax (Math: Subtotal * 0.08)
3. Column: Total (Math: Subtotal + Tax)

Column Types Overview

Basic Columns (Data Storage)

Type	Description	Use Case
Text	String data	Names, descriptions
Number	Numeric values	Prices, quantities
Boolean	True/False	Flags, toggles
Image	Image URL	Profile photos, product images
Date & Time	Timestamps	Due dates, created at
URL	Web links	External resources
Row ID	Unique identifier	Auto-generated ID
Rich Text	Formatted text	Long descriptions
Email	Email addresses	Contact info
Phone Number	Phone format	Contact info
Duration	Time duration	Task duration
Emoji	Emoji picker	Reactions, status
Multiple files	File array	Attachments
Multiple images	Image array	Photo galleries

Computed Columns (Calculations)

Type	Description	Use Case
Math	Arithmetic calculations	Totals, percentages
Template	Text concatenation	Display names, labels
If-Then-Else	Conditional logic	Status labels, flags
Query	Query other tables	Cross-table data
Relation	Link rows between tables	Relationships
Lookup	Get values via relation	Related data
Rollup	Aggregate related data	Sums, counts, averages
Single Value	One value from relation	First/last related item
Joined List	Array to text	Comma-separated list
Split Text	Text to array	Parse delimited data
Make Array	Create array	Multiple values
Distance	Geographic distance	Location calculations
Generate Image	Create images	Dynamic graphics
Construct URL	Build URLs	Dynamic links

AI Columns (Powerful!)

Glide AI columns run inference on your data automatically. Look for opportunities to add these to make apps more useful.

Type	Description	Use Case
Generate Text	AI text generation	Summaries, descriptions, responses, recommendations
Image to Text	Extract info from images	Receipt scanning, document OCR, image analysis
Document to Text	Extract text from docs	PDF parsing, document summarization
Audio to Text	Transcribe audio	Voice notes, meeting recordings
Text to Boolean	AI classification	Sentiment analysis, spam detection, yes/no questions
Text to Choice	AI categorization	Auto-tagging, priority assignment, category detection
Text to JSON	Extract structured data	Form parsing, entity extraction
Text to Number	Extract numbers	Data extraction from text
Text to Date	Parse dates	Natural language date parsing
Text to Texts	Split into multiple	List extraction, keyword extraction

AI Column Ideas by App Type

App Type	AI Enhancement Ideas
Task Management	Auto-prioritize tasks, summarize long descriptions, extract due dates from text
Inventory	Generate product descriptions, extract info from product images
CRM	Summarize customer notes, sentiment analysis on feedback, auto-categorize leads
Content/Documents	Summarize documents, extract key points, auto-tag content
Support/Tickets	Auto-categorize issues, suggest responses, priority detection
Expense Tracking	Extract data from receipt photos, categorize expenses

Integration Columns

Category	Columns
AI Services	Claude, OpenAI, Google Gemini, OpenRouter, Replicate
Google	Google Cloud, Cloud Vision, Google Maps
Data	Call API, JSON, CSV, XML
Utilities	Construct URL, Run Javascript Code
Services	Clearbit, Giphy, Gravatar, Hubspot, Pexels, Short.io, Yelp, ZenRows, OpenGraph.io, Radar
App	App special values, Browser, Device Info, Data Structures

Creating Columns via UI

Adding a Column (Keyboard Shortcut - Recommended)

Fastest method: Use keyboard shortcut with browser automation

1. Navigate to the Data Editor (Data tab)
2. Click on the table where you want to add a column
3. Press CMD+SHIFT+ENTER (macOS) or CTRL+SHIFT+ENTER (Windows)
4. Type the column Name
5. Select the Type from dropdown (required - commits the name)
6. Configure type-specific options
7. Click Save

Why this method:

• Much faster than clicking through UI menus
• Works reliably with browser automation
• Direct keyboard access to column creation

Adding a Column (Manual Method)

Alternative UI-based approach:

1. Go to Data Editor (Data tab)
2. Click any column header
3. Select "Add column right"
4. Configure:
   • Name: Column name
   • Type: Select from dropdown (searchable)
   • Type-specific options
5. Click Save

Note: Keyboard shortcut method is preferred for automation workflows.

Column Type Picker

The Type dropdown is organized into categories:

• Basic - Storage types
• Computed - Calculation types
• AI - AI-powered processing
• Integrations - External services

Type in the search box to filter.

Relation & Lookup Pattern

This is the most common pattern for connecting data:

Step 1: Create Relation Column

• Creates a link between two tables
• Match rows based on a key column
• Can be single or multiple relations

Step 2: Create Lookup Column

• References the Relation column
• Pulls specific column values from related rows
• Example: Get manager's phone number via Employee->Manager relation

Step 3: Create Rollup Column (if aggregating)

• References the Relation column
• Aggregates values: Count, Sum, Average, Max, Min, etc.
• Example: Count of tasks assigned to employee

Math Column Syntax

Math columns support:

• Basic arithmetic: +, -, *, /
• Column references: Click to insert column name
• Functions: Check Glide docs for available functions
• Parentheses for order of operations

Example: (Price * Quantity) * (1 + TaxRate)

If-Then-Else Pattern

Structure:

IF [condition]
THEN [value if true]
ELSE [value if false]

Can be nested for multiple conditions:

IF Status = "Overdue"
THEN "!"
ELSE IF Status = "Due Today"
THEN "Today"
ELSE ""

Template Column Syntax

Templates use replacement syntax:

Hello, {Name}! You have {TaskCount} tasks.

Reference any column by wrapping its name in curly braces.

Glide Big Tables vs Native Tables

Native Tables (Glide Tables)

• Built into every app
• Good for small-medium data
• Full computed column support
• Cannot be shared between apps

Big Tables

• Separate from apps (team-level)
• Handles large datasets
• Required for API v2 access
• Can be shared across multiple apps

Sharing Data Between Apps (Big Tables)

One of Glide's powerful features is linking the same Big Table to multiple apps. This enables:

• Shared data across related apps
• Central data management
• Consistent user experiences

How to Link Shared Tables

1. Go to Data Editor (Data tab)
2. Find Data Sources section in left sidebar
3. Click on your team name (e.g., "SpaceX")
4. A Link Tables panel appears showing:
   • All Big Tables in your team
   • Apps Linked count for each table
   • Last Modified date
   • Searchable table list
5. Check the tables you want to link
6. Click Link Table button

Viewing Linked Tables

The "Apps Linked" column shows how many apps share each table. Click to see which apps use a table.

Use Cases for Shared Tables

Pattern	Description
Central Users	Same Users table across all apps
Shared Products	Product catalog used by multiple apps
Common Reference	Departments, Locations shared everywhere
Activity Logs	Central logging from multiple apps

Data Architecture Tips

1. Plan table sharing upfront - Decide which data should be centralized
2. Use Big Tables for shared data - Native tables can't be shared
3. Consistent column naming - Makes relations easier across apps
4. Single source of truth - Avoid duplicating data in multiple tables

API Access for Data Operations

For programmatic data operations, use the Glide API v2:

• Base URL: https://api.glideapps.com/
• Works only with Big Tables
• Get API token from: Data Editor > Show API > Copy secret token

See the api skill for detailed API usage.

Best Practices

1. Name columns clearly - Use descriptive names that indicate purpose
2. Create intermediate columns - Break complex calculations into steps
3. Use Relations wisely - They're the foundation of data relationships
4. Consider user-specific columns - For per-user data storage
5. Document your data model - Use the Description field
6. Test calculations - Verify with sample data before going live

Documentation

• Data Editor Overview
• Computed Columns
• Relations
• Big Tables