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Getting Started with FlowScope

FlowScope is a privacy-first SQL lineage engine that analyzes SQL queries to produce detailed lineage graphs showing how tables, CTEs, and columns flow through data transformations. All processing happens locally in your browser.

Your First Analysis

Section titled “Your First Analysis”

The fastest way to try FlowScope is through the web app at flowscope.pondpilot.io.

Step 1: Open the Web App

Section titled “Step 1: Open the Web App”

Navigate to flowscope.pondpilot.io. No account or installation required.

Step 2: Enter Your SQL

Section titled “Step 2: Enter Your SQL”

Paste this example query into the SQL editor:

WITH monthly_sales AS (
    SELECT
        customer_id,
        DATE_TRUNC('month', order_date) AS month,
        SUM(amount) AS total_amount
    FROM orders
    GROUP BY customer_id, DATE_TRUNC('month', order_date)
)
SELECT
    c.name,
    c.email,
    ms.month,
    ms.total_amount
FROM monthly_sales ms
JOIN customers c ON ms.customer_id = c.id
WHERE ms.total_amount > 1000;

Step 3: View the Lineage Graph

Section titled “Step 3: View the Lineage Graph”

FlowScope analyzes your query and displays an interactive lineage graph:

  • Tables appear as nodes showing the table name and columns
  • Arrows show how data flows from source tables through transformations
  • CTEs like monthly_sales appear as intermediate nodes

Step 4: Explore the Visualization

Section titled “Step 4: Explore the Visualization”
  • Click a node to see its details and connected columns
  • Hover over an edge to see the column-level lineage
  • Use the controls to zoom, pan, and fit the graph to view
  • Toggle views between table-level and column-level lineage

Understanding the Results

Section titled “Understanding the Results”

In the example above, FlowScope shows:

  1. Source Tables: orders and customers are the upstream data sources
  2. CTE: monthly_sales aggregates order data by customer and month
  3. Final Output: The SELECT produces four columns from the join
  4. Column Lineage: total_amount traces back to orders.amount through SUM()

Selecting a Dialect

Section titled “Selecting a Dialect”

Click the dialect selector to match your SQL syntax:

  • PostgreSQL - Default, covers most standard SQL
  • Snowflake - Snowflake-specific functions and syntax
  • BigQuery - Google BigQuery SQL dialect
  • DuckDB - DuckDB analytical SQL
  • MySQL - MySQL syntax variations
  • Redshift - Amazon Redshift

Selecting the correct dialect ensures accurate parsing of dialect-specific functions and syntax.

Working with Multiple Statements

Section titled “Working with Multiple Statements”

FlowScope can analyze files with multiple SQL statements. Each statement is analyzed separately, with lineage tracked across statements that reference the same tables.

-- Statement 1: Create staging table
CREATE TABLE staging_orders AS
SELECT * FROM raw_orders WHERE status = 'completed';


-- Statement 2: Create summary
SELECT customer_id, COUNT(*) as order_count
FROM staging_orders
GROUP BY customer_id;

Providing Schema Context

Section titled “Providing Schema Context”

For more accurate column resolution, especially with SELECT *, you can provide schema information:

  1. Click the Schema tab
  2. Paste CREATE TABLE statements or connect to a database
  3. FlowScope uses this metadata to resolve wildcards and validate column references
-- Example schema input
CREATE TABLE orders (
    id INT,
    customer_id INT,
    amount DECIMAL(10,2),
    order_date DATE
);

Next Steps

Section titled “Next Steps”