The Complete Guide to xlanalysis: From Excel to Interactive Dashboards in Minutes

Transform your Excel files into powerful, shareable analytics dashboards without any coding knowledge. This comprehensive guide walks you through every feature of xlanalysis, from signup to sharing your insights with the world.

Introduction: Why xlanalysis?

xlanalysis is a powerful, Excel-first analytics platform that transforms your spreadsheets into interactive dashboards—no database setup, no complex integrations, just your Excel files and powerful insights.

What Makes xlanalysis Special?

• Excel-Only Focus: Upload your .xlsx files directly—no database connections needed
• Zero Configuration: Automatic table creation, type inference, and relationship detection
• SQL-Powered: Write custom queries or use visual tools—your choice
• Power BI-Like Experience: Professional dashboards with drag-and-drop simplicity
• Instant Sharing: Share dashboards with secure links—no accounts required for viewers
• Embedded Analytics: DuckDB engine means your data stays fast and local

Whether you're a business analyst, data enthusiast, or team lead, xlanalysis makes advanced analytics accessible to everyone.

Getting Started: Sign Up and Create Your First Project

Step 1: Create Your Account

1. Navigate to the Sign Up Page

• Visit the xlanalysis homepage
• Click the "Sign Up" button in the top navigation

1. Fill in Your Details

• Enter your full name
• Provide a valid email address (you'll need to verify it)
• Create a strong password (minimum 8 characters)
• Click "Create Account"

1. Verify Your Email

• Check your inbox for the verification email
• Click the verification link
• You'll be redirected to the sign-in page

1. Sign In

• Enter your email and password
• Click "Sign In"
• You'll be taken to the Projects page

Step 2: Create Your First Project

Projects in xlanalysis are isolated workspaces where you organize your data, models, and dashboards. Think of them as separate analytics environments.

1. Access the Projects Page

• After signing in, you'll land on the Projects page
• If you're new, you'll see an empty state with a "Create Project" button

1. Create a New Project

• Click "Create Project" or the "+" button
• Enter a project name (e.g., "Q4 Sales Analysis", "Marketing Campaigns")
• Optionally add a description
• Click "Create"

1. Select Your Active Project

• Your new project appears in the projects list
• Click on it to make it active
• The active project is highlighted and used for all data operations

Pro Tip: Create separate projects for different departments, time periods, or analysis types. Each project maintains its own data isolation.

Upload Your Data: Excel Files Made Simple

xlanalysis automatically converts your Excel sheets into queryable tables. Here's how to get your data in.

Step 1: Navigate to the Data Section

1. Open the Data Workspace

• Click "Data" in the left sidebar
• You'll see the Data Workspace with three main sections:
• Data: File upload and SQL editor
• Model: Relationships and measures
• Report: Dashboard builder (covered later)

Step 2: Upload Your Excel File

1. Choose Your Upload Method

• Method 1: Click "Browse Excel" and select your file
• Method 2: Drag and drop your .xlsx file into the upload area

1. File Requirements

• Format: .xlsx files only (Excel 2007+)
• Size Limit: Up to 50MB per file
• Row Limit: 200,000 rows per sheet
• Multiple Files: You can upload multiple files to the same project

1. Upload Process

• Once you select a file, you'll see a progress indicator
• The system processes your file in stages:
• Reading file structure
• Detecting sheets
• Creating tables
• Inferring data types
• Detecting primary keys

1. Upload Success

• After processing, you'll see a success message
• Each sheet in your Excel file becomes a separate table
• Tables appear in the "Tables" panel on the left

Step 3: Understand Your Data

1. View Table Metadata

• Click on any table name in the Tables panel
• You'll see:
• Table name: Derived from the sheet name
• Row count: Number of records
• Columns: List of all columns with their data types
• Primary key: Auto-detected or manually set

1. Data Type Inference

• xlanalysis automatically detects:
• VARCHAR: Text data
• DOUBLE: Decimal numbers
• INTEGER: Whole numbers
• DATE: Date values
• BOOLEAN: True/False values
• Column names are normalized to snake_case for SQL compatibility

1. Preview Your Data

• Use the SQL editor (next section) to preview table contents
• Or wait until you build dashboards to visualize the data

Pro Tip: Name your Excel sheets descriptively—they become table names. Avoid special characters and spaces for best results.

Query Your Data: SQL Editor for Power Users

xlanalysis includes a powerful SQL editor powered by Monaco (the same editor used in VS Code). Write queries to explore, filter, and analyze your data.

Step 1: Access the SQL Editor

1. Open the SQL Editor

• In the Data section, find the SQL Editor panel
• It features syntax highlighting, autocomplete, and error detection

Step 2: Write Your First Query

1. Basic SELECT Query

SELECT * FROM "your_table_name" LIMIT 10;

• Replace "your_table_name" with your actual table name
• Use quotes around table names if they contain special characters
• LIMIT 10 shows only the first 10 rows

1. Filter Data

SELECT * FROM "sales_data" 
WHERE amount > 1000 
ORDER BY date DESC;

1. Aggregate Data

SELECT 
  category,
  SUM(amount) as total_sales,
  COUNT(*) as order_count
FROM "sales_data"
GROUP BY category
ORDER BY total_sales DESC;

1. Join Tables

SELECT 
  o.order_id,
  o.amount,
  c.customer_name
FROM "orders" o
JOIN "customers" c ON o.customer_id = c.id;

Step 3: Execute and View Results

1. Run Your Query

• Click "Run Query" or press Ctrl+Enter (Windows) / Cmd+Enter (Mac)
• Results appear in a table below the editor

1. Query Features

• Read-Only: All queries are read-only (no INSERT, UPDATE, DELETE)
• Timeout: Queries timeout after 10 seconds
• Error Messages: Clear error messages help debug issues
• Result Export: Copy results or use them in dashboards

1. Query History

• Your recent queries are saved automatically
• Access them from the query history panel

Pro Tip: Test your queries in the SQL editor before using them in dashboards. This helps you verify data and performance.

Model Your Data: Relationships, Measures, and Calculated Columns

The Model workspace is where you define how your data connects and create reusable calculations. This is the foundation for powerful dashboards.

Part 1: Define Relationships

Relationships connect tables so you can join data across multiple sources.

Step 1: Access the Model Graph

1. Open the Model Section

• In the Data workspace, scroll to the "Model" section
• You'll see the Model Graph—a visual canvas for relationships

Step 2: Create Relationships Visually

1. Start a Connection

• Click on a table in the graph
• The table highlights, indicating you're starting a connection
• A tag appears: "Connecting from: [table_name]"

1. Complete the Connection

• Click on another table to connect to
• The Relationship Form modal opens

1. Configure the Relationship

• From Table: The source table (already selected)
• From Column: Choose the foreign key column
• To Table: The target table (already selected)
• To Column: Choose the primary key column
• Relationship Type: Select one of:
• One-to-One: Each record in Table A matches one record in Table B
• One-to-Many: One record in Table A matches many in Table B
• Many-to-One: Many records in Table A match one in Table B
• Many-to-Many: Many-to-many relationships (shown with dashed lines)
• Click "Create"

1. View Relationships

• Relationships appear as lines connecting tables
• Hover over a line to highlight it
• Double-click a relationship line to edit or delete it

Step 3: Edit or Delete Relationships

1. Edit a Relationship

• Double-click any relationship line
• The Relationship Form opens with current settings
• Make changes and click "Update"

1. Delete a Relationship

• Double-click a relationship line
• In the Relationship Form, click "Delete"
• Confirm the deletion
• The relationship is removed from the graph

Pro Tip: Define relationships before creating measures. This ensures your calculations work correctly across related tables.

Part 2: Create Measures

Measures are reusable calculations (like SUM, AVG, COUNT) that you can use in dashboards.

Step 1: Open the Measures Panel

1. Access Measures

• In the Model section, find the "Measures" panel
• Click "New Measure" to create your first measure

Step 2: Create a Measure

1. Fill in the Measure Form

• Measure Name: A descriptive name (e.g., "Total Revenue", "Average Order Value")
• Formula: SQL aggregation expression
• Examples:
• SUM(table_name.amount) - Total sum
• AVG(table_name.price) - Average value
• COUNT(table_name.id) - Count of records
• SUM(table_name.amount) / COUNT(table_name.id) - Calculated ratio
• Format: Choose how to display the value:
• Currency: $1,234.56
• Number: 1,234.56
• Percentage: 12.34%
• Decimal: 1.23
• Description: Optional description for documentation
• Click "Create Measure"

1. Example Measures

-- Total Sales
SUM(sales_data.amount)

-- Average Order Value
SUM(orders.total) / COUNT(orders.id)

-- Year-over-Year Growth
(SUM(sales_2024.amount) - SUM(sales_2023.amount)) / SUM(sales_2023.amount)

Step 3: Manage Measures

1. Edit a Measure

• Click the edit icon next to any measure
• Update the formula, format, or description
• Click "Update"

1. Delete a Measure

• Click the delete icon
• Confirm deletion
• Note: This won't affect dashboards that use the measure, but those visuals will show an error

1. Preview a Measure

• Click the preview icon to see the calculated value
• Useful for testing before using in dashboards

Pro Tip: Create commonly used measures first (Total Revenue, Total Orders, etc.). You can reuse them across multiple dashboards.

Part 3: Create Calculated Columns

Calculated columns add new columns to your tables based on formulas.

Step 1: Open Calculated Columns

1. Access Calculated Columns

• In the Model section, find the "Calculated Columns" panel
• Click "New Calculated Column"

Step 2: Create a Calculated Column

1. Configure the Column

• Table: Select the table to add the column to
• Column Name: Name for the new column
• Expression: SQL expression that calculates the value
• Examples:
• CONCAT(first_name, ' ', last_name) - Combine text
• YEAR(date_column) - Extract year
• CASE WHEN amount > 1000 THEN 'High' ELSE 'Low' END - Conditional logic
• Description: Optional description
• Click "Create"

1. Preview Calculated Column

• Use the preview feature to see sample values
• Verify the calculation works as expected

Pro Tip: Calculated columns are computed when queried, so they're always up-to-date with your data.

Part 4: Generate Calendar Table (Time Intelligence)

xlanalysis can generate a calendar table for time-based analysis.

1. Access Calendar Generation

• In the Model section, find the "Time Intelligence" panel
• Click "Generate Calendar Table"

1. Configure Date Range

• Start Date: Beginning of your date range
• End Date: End of your date range
• Fiscal Year Start: Optional fiscal year configuration
• Click "Generate"

1. Use the Calendar Table

• The calendar table includes:
• Date, year, quarter, month, day
• Day of week, day of year, week number
• Is weekend/weekday flags
• Year-month, year-quarter, year-week strings
• Month and day names
• Join this table with your date columns for time intelligence

Pro Tip: Generate a calendar table that covers your entire data range plus a few years forward for forecasting.

Build Dashboards: Visual Analytics Made Easy

Dashboards are where your data comes to life. Create interactive visuals, arrange them on a canvas, and tell your data story.

Step 1: Navigate to Dashboards

1. Access the Dashboards Page

• Click "Dashboards" in the left sidebar
• You'll see a list of all dashboards for your active project
• Click "New Dashboard" to create one

Step 2: Create a New Dashboard

1. Open the Dashboard Builder

• Click "New Dashboard" or select an existing dashboard
• The dashboard builder opens with:
• Canvas: The main area where visuals are placed
• Visual Library: Panel on the right with visual types
• Properties Panel: Configuration options
• Saved Dashboards: List of saved dashboards

1. Name Your Dashboard

• Enter a descriptive name (e.g., "Sales Overview", "Marketing Performance")
• The name is saved when you save the dashboard

Step 3: Add Visuals to Your Dashboard

Visual Types Available

1. Table

• Display data in a tabular format
• Best for: Detailed data views, lists, comparisons

1. Bar Chart

• Horizontal or vertical bars
• Best for: Comparing categories, rankings

1. Line Chart

• Line graph showing trends over time
• Best for: Time series, trends, continuous data

1. Area Chart

• Filled area under a line
• Best for: Cumulative values, stacked trends

1. Pie Chart

• Circular chart showing proportions
• Best for: Part-to-whole relationships

1. Donut Chart

• Pie chart with a hole in the center
• Best for: Part-to-whole with center KPI

1. KPI Card

• Single value display
• Best for: Key metrics, totals, averages
• Can use measures you created in the Model section

Adding a Visual

1. Select a Visual Type

• Click on any visual type in the Visual Library
• A new visual appears on the canvas

1. Configure the Visual

• Option 1: Table Selection (Easier)
• Select a table from the dropdown
• Choose columns to display
• The visual automatically generates a query
• Option 2: Custom SQL (More Control)
• Write a custom SQL query
• Use the SQL editor with syntax highlighting
• Test your query before saving

1. For KPI Visuals

• You can use a measure (created in Model section)
• Or write a custom SQL query that returns a single value
• Example: SELECT SUM(amount) FROM sales_data

1. Save the Visual

• Click "Save Visual"
• The query executes and data appears in the visual

Step 4: Arrange and Resize Visuals

1. Move Visuals

• Click and drag any visual to reposition it
• Visuals snap to a grid for alignment

1. Resize Visuals

• Click and drag the resize handles (corners/edges)
• Visuals maintain aspect ratio

1. Delete Visuals

• Click the delete icon on a visual
• Confirm deletion
• The visual is removed from the canvas

Step 5: Save Your Dashboard

1. Save the Dashboard

• Click "Save Dashboard" in the top toolbar
• Enter or confirm the dashboard name
• Click "Save"
• Your dashboard is now persisted

1. Load a Saved Dashboard

• In the "Saved Dashboards" panel, click any dashboard name
• The dashboard loads with all visuals
• Queries re-execute to show current data

Step 6: Build a Complete Dashboard

Example: Sales Dashboard

1. Add a KPI for Total Revenue

• Add a KPI visual
• Use measure: "Total Revenue" (created earlier)
• Position it at the top

1. Add a Bar Chart for Sales by Category

• Add a Bar Chart visual
• Select "sales_data" table
• X-axis: category
• Y-axis: amount (SUM)

1. Add a Line Chart for Sales Over Time

• Add a Line Chart visual
• Select "sales_data" table
• X-axis: date
• Y-axis: amount (SUM)

1. Add a Table for Top Products

• Add a Table visual
• Write SQL:

SELECT product_name, SUM(amount) as total_sales
FROM sales_data
GROUP BY product_name
ORDER BY total_sales DESC
LIMIT 10;

1. Arrange and Save

• Position visuals for best layout
• Save the dashboard

Pro Tip: Start with KPIs at the top, then add charts below. Use tables for detailed data. This creates a natural flow from summary to detail.

Share Your Insights: Collaborate and Present

Once your dashboard is ready, share it with your team, stakeholders, or clients. xlanalysis makes sharing secure and simple.

Step 1: Access Dashboard Sharing

1. Open Your Dashboard

• Navigate to the Dashboards page
• Open the dashboard you want to share

1. Find the Share Button

• Look for the "Share" button or icon in the dashboard toolbar
• Click it to open sharing options

Step 2: Generate a Share Link

1. Create Share Link

• Click "Generate Share Link"
• A secure, unique link is created
• The link is copied to your clipboard automatically

1. Share Link Features

• No Login Required: Recipients don't need an xlanalysis account
• Read-Only: Viewers can see the dashboard but not edit it
• Secure: Each link is unique and can be revoked
• Always Up-to-Date: Shows current data when accessed

Step 3: Share Your Dashboard

1. Copy the Link

• The share link is automatically copied
• Or click "Copy Link" to copy it again
• Format: https://your-domain.com/share/[unique-token]

1. Distribute the Link

• Email: Send the link via email
• Slack/Teams: Share in team channels
• Presentations: Include in presentations or reports
• Documentation: Add to internal wikis or docs

1. Test the Link

• Open the link in an incognito/private window
• Verify the dashboard displays correctly
• Check that all visuals load properly

Step 4: Manage Shared Dashboards

1. View Active Shares

• In the dashboard, see how many times it's been shared
• View share history if available

1. Revoke Access

• If needed, you can revoke a share link
• The link will no longer work
• Generate a new link if you need to share again

Pro Tip: Share links are perfect for:

• Weekly/monthly reports to stakeholders
• Client presentations
• Team dashboards
• Executive summaries

Pro Tips and Best Practices

Data Management

1. Organize Your Projects

• Create separate projects for different departments or time periods
• Use descriptive project names
• Keep related data together

1. Excel File Best Practices

• Use clear, descriptive sheet names
• Ensure first row contains column headers
• Remove empty rows/columns before uploading
• Keep data types consistent within columns

1. Table Naming

• Sheet names become table names
• Avoid special characters
• Use underscores instead of spaces

SQL Queries

1. Performance Tips

• Use LIMIT when exploring large datasets
• Add WHERE clauses to filter early
• Use indexes (primary keys) for joins
• Avoid SELECT * on large tables

1. Query Organization

• Save complex queries as measures
• Document queries with comments
• Test queries in SQL editor before using in dashboards

Relationships

1. Best Practices

• Define relationships before creating measures
• Use proper foreign key/primary key pairs
• Choose correct relationship types
• Document relationships with descriptions

1. Common Patterns

• Orders → Customers: Many-to-One
• Products → Categories: Many-to-One
• Orders → Order Items: One-to-Many

Measures

1. Naming Conventions

• Use clear, descriptive names
• Prefix with category if needed (e.g., "Sales - Total Revenue")
• Avoid abbreviations unless standard

1. Reusability

• Create common measures first
• Use measures in multiple dashboards
• Update measures to update all dashboards

Dashboards

1. Layout Tips

• Start with KPIs at the top
• Group related visuals together
• Use consistent sizing for similar visuals
• Leave white space for readability

1. Visual Selection

• KPIs: For single important metrics
• Bar Charts: For comparing categories
• Line Charts: For trends over time
• Pie Charts: For part-to-whole relationships
• Tables: For detailed data

1. Performance

• Limit visuals per dashboard (10-15 max)
• Use efficient queries
• Avoid overly complex calculations in visuals

Sharing

1. Security

• Only share dashboards with trusted recipients
• Revoke links when no longer needed
• Don't share sensitive data without encryption

1. Communication

• Provide context when sharing
• Explain what the dashboard shows
• Include date ranges or filters applied

Troubleshooting Common Issues

Upload Issues

Problem: File upload fails

• Solution: Check file size (max 50MB), ensure it's .xlsx format, verify file isn't corrupted

Problem: Some sheets not appearing

• Solution: Check row count (max 200k rows per sheet), ensure sheets have data

Problem: Column types incorrect

• Solution: Ensure consistent data types in Excel columns, re-upload if needed

SQL Query Issues

Problem: Query times out

• Solution: Add LIMIT clause, add WHERE filters, optimize query structure

Problem: "Table does not exist" error

• Solution: Check table name spelling (case-sensitive), use quotes around table names

Problem: Join not working

• Solution: Verify relationships are defined, check column names match, ensure data types are compatible

Relationship Issues

Problem: Can't create relationship

• Solution: Verify columns exist, check data types match, ensure primary key is set

Problem: Relationship not working in queries

• Solution: Verify relationship type is correct, check column mappings

Dashboard Issues

Problem: Visual not showing data

• Solution: Check SQL query syntax, verify table/column names, test query in SQL editor first

Problem: Visual not updating

• Solution: Refresh the dashboard, re-save the visual, check data source

Problem: Dashboard loads slowly

• Solution: Reduce number of visuals, optimize queries, add filters

Sharing Issues

Problem: Share link not working

• Solution: Verify link is correct, check if link was revoked, ensure dashboard exists

Problem: Recipients can't see dashboard

• Solution: Verify link was copied correctly, check internet connection, try in different browser

Conclusion: Your Analytics Journey Starts Here

Congratulations! You've learned how to use xlanalysis from signup to sharing. You now know how to:

• Create projects and organize your data
• Upload Excel files and convert them to queryable tables
• Write SQL queries to explore your data
• Model relationships and create measures
• Build interactive dashboards with multiple visuals
• Share your insights with secure links

Next Steps

1. Upload Your First Excel File: Start with a file you know well
2. Create a Simple Dashboard: Build a dashboard with 2-3 visuals
3. Experiment with Measures: Create reusable calculations
4. Share with Your Team: Get feedback and iterate

Resources

• SQL Documentation: Learn SQL basics if needed
• Community: Join discussions and get help
• Updates: Follow for new features and improvements

Start Your Analytics Journey Today

xlanalysis makes advanced analytics accessible to everyone. Whether you're analyzing sales data, tracking marketing campaigns, or monitoring operations, xlanalysis helps you turn Excel files into actionable insights.

Ready to get started? Sign up for free and upload your first Excel file today!

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This guide covers xlanalysis features as of the latest version. Features may evolve, so check the documentation for the most current information.