Stairway to Snowflake Level 4 - Introducing Snowsight, Snowflake’s Web UI
This next level of the Stairway to Snowflake looks at the Snowsight UI and what you can accomplish with it.
This next level of the Stairway to Snowflake looks at the Snowsight UI and what you can accomplish with it.
Snowflake has its own CLI tool: SnowSQL. In this level of the Stairway Series learn how to work with this dialect in Snowflake and Visual Studio Code.
In this next level of the Stairway to Snowflake, learn about creating and dropping databases, with some options for cloning from different sources.
In this next level of the Stairway to Snowflake we examine the wide variety of table types that exist in the platform.
Today Steve talks about the concept of what a failure is when deploying changes.
Real-time data ingestion has become essential for modern analytics and operational intelligence. Organizations across industries need to process data streams from IoT sensors, financial transactions, and application events with minimal latency. Snowflake offers two robust approaches to meet these real-time data needs: Snowpipe for near-real-time file-based streaming and Direct Streaming via Snowpark API for true real-time data integration.
Tony describes in more detail the SIMPLE recovery model, and the way it works, its advantages and disadvantages.
Validate all of your settings and be prepared to make some changes during your migration process. Most of the incompatible options make sense when you think about the purpose of SQL MI – it is controlled by Microsoft. Hardware settings, local file access, high-availability settings, and auditing are configured differently or completely disabled.
Learn a few ways to improve performance in your Azure SQL Databases through better indexing, partitioning, and columnstore index consideration.
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Comments posted to this topic are about the item Fun with JSON II
Comments posted to this topic are about the item Changing Data Types
Comments posted to this topic are about the item Answering Questions On Dropped Columns
I have some data in a table:
CREATE TABLE #test_data
(
id INT PRIMARY KEY,
name VARCHAR(100),
birth_date DATE
);
-- Step 2: Insert rows
INSERT INTO #test_data
VALUES
(1, 'Olivia', '2025-01-05'),
(2, 'Emma', '2025-03-02'),
(3, 'Liam', '2025-11-15'),
(4, 'Noah', '2025-12-22');
If I run this query, how many rows are returned?
SELECT t1.[key] AS row,
t2.*
FROM OPENJSON(
(
SELECT t.* FROM #test_data AS t FOR JSON PATH
)
) t1
CROSS APPLY OPENJSON(t1.value) t2; See possible answers