Level 1 of the Stairway to Synapse Analytics - Create a Synapse Workspace
In this first level of the Stairway to Synapse Analytics, we learn how to set up a new workspace and add data files.
2025-06-06 (first published: 2024-07-03)
1,387 reads
Sucharita Das
Level 2 of the Stairway to Synapse Analytics: Analyze Data in Storage Account using the Serverless SQL pool
In this second level of the Stairway to Synapse, we learn how to create external tables and query data that is stored in our data storage using the serverless pool.
2025-06-06 (first published: 2024-08-14)
1,031 reads
Level 3 of the Stairway to Synapse Analytics: Analyze Data Using a Spark Pool
Introduction In Level 1 of this series, I discussed Synapse Analytics basics and the steps for creation of the Synapse Workspace. In Level 2, data analysis was done on Data Lake files using Serverless SQL Pool. In Level 3, I will analyze data from the files uploaded in Data Lake container using a Spark Pool. I will […]
2025-06-06 (first published: 2024-09-18)
915 reads
Level 4 of the Stairway to Synapse Analytics: Create and Use a Delta Lake
Introduction In Level 1 of this series, I discussed Synapse Analytics basics and the steps for creating the Synapse Workspace. In Level 2, we analyzed Data Lake files using the Serverless SQL Pool. In Level 3, we analyzed Data Lake files using the Spark Pool. In Levels 4 and level 5, I will discuss the Delta […]
2025-06-06 (first published: 2024-12-18)
1,869 reads
Level 5 of the Stairway to Synapse Analytics: create and use Delta Lake - Part 2
This next article in the Stairway to Synapse looks at Delta tables and processing streaming data.
2025-06-06 (first published: 2025-04-09)
919 reads
Level 6 of the Stairway to Synapse Analytics: Dedicated SQL Pool
This next level of the Stairway to Synapse Analysis Services looks at the Dedicated SQL Pool.
2025-06-06 (first published: 2025-05-07)
666 reads
GIT Configuration and Automated Release for Azure Data Factory
Learn a step-by-step method to save your ADF pipelines in Git and automatically release new changes to test and production.
2024-09-23 (first published: 2023-10-16)
2,689 reads
Using Machine Learning Pipeline Execution Activity in Azure Data Factory
This article shows how one can run a machine learning activity in an Azure Data Factory (ADF) pipeline.
2024-05-13
1,117 reads
Ingest and Retrieve data from an ADX Cluster Using Python
Learn how to query data in Azure Data Explorer using Python.
2024-05-06
1,376 reads
Trigger the Execution of an ADF Pipeline from an Email
Learn how you can configure an Azure Data Factory pipeline that is triggered by an email being sent to an address.
2023-11-03 (first published: 2023-10-27)
4,668 reads
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Question of the Day
Fun with JSON I
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 *
FROM OPENJSON(
(
SELECT t.* FROM #test_data AS t FOR JSON PATH
)
) t; See possible answers