Skip to main content
The No-Code Query Builder empowers users—regardless of SQL knowledge—to visually create, customize, and run data queries. This intuitive interface delivers quick business insights through a guided, code-free experience, making data analysis accessible to analysts, product managers, and business users.
Transform your data exploration with visual query construction. No SQL required—just point, click, and analyze.

Overview

No Code Query Builder

2
The No-Code Query Builder is a visual interface that enables users to construct database queries through guided steps rather than writing code. It bridges the gap between technical and non-technical users by providing:
  • Visual Query Construction: Build queries through point-and-click interface
  • Natural Language Input: Ask questions in plain English
  • Instant Results: See data immediately as you build
  • SQL Transparency: View generated SQL for learning and refinement
  • Save & Share: Preserve queries and visualizations for team collaboration
The Query Builder is designed for diverse user personas:Business Analysts
  • Create reports without technical dependencies
  • Explore data trends and patterns quickly
  • Build dashboards for stakeholder presentations
Product Managers
  • Analyze user behavior and product metrics
  • Track feature adoption and engagement
  • Generate insights for data-driven decisions
Marketing Teams
  • Segment customer data for campaigns
  • Track conversion metrics and attribution
  • Analyze campaign performance across channels
SQL Beginners
  • Learn query construction through visual guidance
  • Understand SQL generation from visual inputs
  • Graduate to advanced SQL writing with confidence

Core Features

Natural Language Analytics Panel

The prominent natural language panel enables intuitive data interaction:Ask Questions Naturally
  • “What are our top-performing products this quarter?”
  • “Show me user engagement trends over the past 30 days”
  • “Which marketing channels drive the most conversions?”
Intelligent Query Interpretation
  • AI understands context and intent from your questions
  • Automatically selects appropriate tables and columns
  • Suggests relevant filters and aggregations
  • Generates optimized SQL queries behind the scenes
Interactive Refinement
  • Ask follow-up questions to drill deeper
  • Modify queries through conversation
  • Get explanations of results and insights

Visual Query Construction

The visual builder follows a logical, guided workflow:1. Data Source Selection
  • Choose your target database from connected sources
  • Browse available databases with clear descriptions
  • See connection status and data freshness indicators
2. Table Selection
  • Pick the primary table for your analysis
  • View table descriptions and row counts
  • See column previews and data types
3. Column Configuration
  • Select specific columns to include in results
  • Choose from available columns with data type indicators
  • Add calculated fields and aggregations
  • Rename columns for clearer output
4. Filter Application
  • Apply conditions to narrow down results
  • Use visual filter builders for different data types
  • Combine multiple filters with AND/OR logic
  • Preview filter effects before execution
5. Join Configuration (Optional)
  • Add related data from other tables
  • Visual join builder with relationship suggestions
  • Support for INNER, LEFT, RIGHT, and FULL OUTER joins
  • Join condition validation and optimization
6. Sorting & Limits
  • Set result ordering (ascending/descending)
  • Configure row limits for performance
  • Multiple sort criteria support
  • Smart defaults based on data types
Aggregation & Grouping
  • Group results by specific columns
  • Apply aggregate functions (COUNT, SUM, AVG, MIN, MAX)
  • Create calculated metrics and ratios
  • Handle null values and edge cases
Date & Time Handling
  • Intelligent date range pickers
  • Relative date filters (“last 30 days”, “this quarter”)
  • Time zone conversion and formatting
  • Date part extraction (year, month, day of week)
Text & String Operations
  • Pattern matching and text search
  • Case-insensitive comparisons
  • String concatenation and formatting
  • Regular expression support for advanced users

Execution & Results

Instant Execution
  • Run queries with a single click
  • Real-time result streaming for large datasets
  • Progress indicators for long-running queries
  • Cancellation support for resource management
Performance Optimization
  • Automatic query optimization suggestions
  • Row limit recommendations based on data size
  • Index usage analysis and recommendations
  • Query cost estimation before execution
Error Handling
  • Clear error messages with suggested fixes
  • Visual indicators for invalid configurations
  • Rollback to previous working configurations
  • AI-powered error resolution assistance
Multiple Display Formats
  • Tabular data grid with sorting and filtering
  • Interactive charts and graphs
  • Summary statistics and data profiles
  • Export options (CSV, JSON, PDF)
Chart Generation
  • Automatic chart type recommendations
  • Customizable visualizations
  • Interactive charts with drill-down capabilities
  • Dashboard-ready widgets
Data Insights
  • Automatic pattern detection
  • Statistical summaries and distributions
  • Anomaly highlighting
  • Trend analysis and forecasting hints

Workflow Examples

Scenario: Analyze checkout events for the past month to understand conversion patterns.Step-by-Step Process:
  1. Data Source: Select “E-commerce Database”
  2. Table: Choose “events” table
  3. Columns: Select event_name, event_timestamp, user_id, product_id, revenue
  4. Filters:
    • event_name = ‘checkout_started’ OR ‘checkout_completed’
    • event_timestamp >= 30 days ago
  5. Grouping: Group by event_name and date
  6. Aggregation: Count events and sum revenue
  7. Sorting: Order by date descending
  8. Visualization: Generate conversion funnel chart
Expected Output: Visual conversion analysis showing checkout completion rates and revenue trends over time.
Scenario: Segment users based on engagement patterns and purchase history.Step-by-Step Process:
  1. Data Source: Select “Customer Database”
  2. Table: Start with “users” table
  3. Joins: Add “orders” and “sessions” tables
  4. Columns: user_id, registration_date, total_orders, session_count, last_activity
  5. Calculations: Create engagement_score and customer_lifetime_value
  6. Filters: Active users in last 90 days
  7. Grouping: Segment by engagement level
  8. Visualization: Create user segment distribution chart
Expected Output: Customer segments with behavioral characteristics and value metrics.
Scenario: Analyze marketing campaign effectiveness across different channels.Step-by-Step Process:
  1. Data Source: Select “Marketing Database”
  2. Table: Choose “campaigns” table
  3. Joins: Connect to “conversions” and “costs” tables
  4. Columns: campaign_name, channel, impressions, clicks, conversions, cost
  5. Calculations: CTR, conversion_rate, ROAS, cost_per_acquisition
  6. Filters: Last quarter campaigns only
  7. Grouping: Group by channel and campaign type
  8. Sorting: Order by ROAS descending
  9. Visualization: Multi-metric performance dashboard
Expected Output: Comprehensive campaign performance analysis with ROI insights.

Advanced Features

Generated SQL Viewing
  • See the SQL query generated from your visual configuration
  • Learn SQL syntax through example
  • Copy generated queries for manual editing
  • Understand query optimization techniques
SQL Editor Integration
  • Seamlessly switch between visual and SQL modes
  • Edit generated SQL directly for advanced customization
  • Visual builder updates when SQL is modified (where possible)
  • Syntax highlighting and auto-completion support
Query Explanation
  • AI-powered explanations of query logic
  • Performance impact analysis
  • Alternative query suggestions
  • Best practices recommendations
Save & Organize
  • Save queries with descriptive names and tags
  • Organize saved queries in folders and categories
  • Version control for query iterations
  • Duplicate and modify existing queries
Team Sharing
  • Share queries with team members
  • Collaborative editing and commenting
  • Role-based access control for sensitive data
  • Usage analytics and adoption tracking
Export & Integration
  • Export results in multiple formats
  • Schedule automated query execution
  • Integrate with BI tools and dashboards
  • API access for programmatic usage
Pre-built Prompts
  • Industry-specific query templates
  • Common business questions and patterns
  • Best practice examples for different use cases
  • Customizable prompt library
Smart Suggestions
  • Context-aware column and filter suggestions
  • Join recommendations based on schema relationships
  • Optimization hints for query performance
  • Data quality warnings and recommendations
Template Management
  • Create custom templates for repeated analyses
  • Share templates across teams
  • Template versioning and updates
  • Usage tracking and optimization

Getting Started

Step 1: Access the Query Builder
  • Navigate to the Query Builder from the main dashboard
  • Select “Visual Builder” mode if prompted
  • Ensure you have proper database permissions
Step 2: Try Natural Language
  • Click in the natural language panel
  • Type a simple question like “Show me all customers from last month”
  • Review the generated query and results
  • Refine using follow-up questions
Step 3: Explore Visual Building
  • Start with data source selection
  • Browse available tables and their descriptions
  • Add a few columns and basic filters
  • Execute your first visual query
Step 4: Save and Share
  • Save your successful query with a descriptive name
  • Add tags for easy discovery
  • Share with team members if needed
  • Explore visualization options
Query Design
  • Start simple and add complexity gradually
  • Use filters early to reduce data volume
  • Test with row limits before removing restrictions
  • Document complex queries with descriptions
Performance Optimization
  • Apply filters before joins when possible
  • Use appropriate row limits for exploration
  • Monitor query execution times
  • Leverage suggested optimizations
Collaboration
  • Use descriptive names for saved queries
  • Add context and documentation for team queries
  • Tag queries by project or use case
  • Share insights and findings with stakeholders

Reference

Feature Comparison Table

FeatureVisual BuilderNatural LanguageSQL Editor
Ease of Use⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐
Flexibility⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐⭐
Learning CurveLowVery LowMedium-High
Query ComplexityMedium-HighMediumUnlimited
Speed for Simple QueriesFastVery FastMedium
Speed for Complex QueriesMediumMediumFast

Keyboard Shortcuts

ActionShortcutDescription
Run QueryCtrl/Cmd + EnterExecute current query configuration
Save QueryCtrl/Cmd + SSave current query and settings
Clear FiltersCtrl/Cmd + KRemove all applied filters
Switch to SQLCtrl/Cmd + Shift + SToggle to SQL editor mode
Add ColumnCtrl/Cmd + +Add new column to selection
Remove ColumnCtrl/Cmd + -Remove selected column

Query Console

Switch to the advanced Query Console for SQL editing and complex operations
I