Get started with materialized lake views

2025-08-24

In this article, you learn how to get started with materialized lake views by creating one in a Microsoft Fabric lakehouse.

Prerequisites

A workspace with a Microsoft Fabric-enabled capacity.
A lakehouse with lakehouse schemas enabled.
Fabric Runtime 1.3. Materialized lake views are compatible with this runtime version.

Create your first materialized lake view

Go to your lakehouse and select Manage materialized lake views.
Select New materialized lake view, and then select New notebook.

A new notebook opens.

Create the sample source tables products and orders. Run the following commands in the notebook:

   CREATE SCHEMA IF NOT EXISTS bronze;

   CREATE TABLE IF NOT EXISTS bronze.products (
    product_id INT,
    product_name STRING,
    price DOUBLE
   );

   INSERT INTO bronze.products VALUES
   (101, 'Laptop', 1200.50),
   (102, 'Smartphone', 699.99),
   (103, 'Tablet', 450.00);


   CREATE TABLE IF NOT EXISTS bronze.orders (
     order_id INT,
     product_id INT,
     quantity INT,
     order_date DATE
    );
   INSERT INTO bronze.orders VALUES
    (1001, 101, 2, '2025-06-01'),
    (1002, 103, 1, '2025-06-02'),
    (1003, 102, 3, '2025-06-03');

Create materialized lake views by using the source tables. Run the following commands in the notebook:

   CREATE SCHEMA IF NOT EXISTS SILVER;

   CREATE MATERIALIZED LAKE VIEW IF NOT EXISTS silver.cleaned_order_data AS
   SELECT 
       o.order_id,
       o.order_date,
       o.product_id,
       p.product_name,
       o.quantity,
       p.price,
       o.quantity * p.price AS revenue
   FROM bronze.orders o
   JOIN bronze.products p
   ON o.product_id = p.product_id;

   CREATE SCHEMA IF NOT EXISTS GOLD;

   CREATE MATERIALIZED LAKE VIEW IF NOT EXISTS gold.product_sales_summary AS
   SELECT
       product_id,
       product_name,
       SUM(quantity) AS total_quantity_sold,
       SUM(revenue) AS total_revenue,
       ROUND(AVG(revenue), 2) AS average_order_value
   FROM
       silver.cleaned_order_data
   GROUP BY
       product_id,
       product_name;

Open the lakehouse explorer to view all created tables and materialized lake views.
In your lakehouse, go to Manage materialized lake views to view the autogenerated lineage.
Schedule the lineage execution.
Select the ongoing run to monitor progress after the schedule starts.
After the run succeeds, the status of the lineage is Completed.