Advantages of Kappa architecture in the Modern Data Stack
A comparison of the lambda and kappa architectures for real time ingestion and analysis of big data.
2023-06-19
5,488 reads
ETL/SSIS/Azure Data Factory
Python 3 Script for Generating SQL Insert Statements from CSV Data
This Python 3 script is designed to take CSV file data pasted into the csv_data variable and generate SQL insert statements that can be used to insert the data into a MySQL database. The script is easy to use and can save you a lot of time when working with large amounts of data.
2023-05-08 (first published: 2023-05-05)
5,739 reads
How to Implement CI/CD in Azure Data Factory (ADF)
Learn how you can use CI/CD with your ADF Pipelines and Azure DevOps using ARM templates.
2023-03-10
13,667 reads
Ingesting Data from Google Drive to Azure Data Lake Gen2 using Azure Data Factory
Learn how to setup, configure and ingest data from Google Drive using Azure Data Factory in this step-by-step article.
2023-02-01
The Art of Data Ingestion - Part 1
Data movement is a fundamental piece of a data engineer’s duties, and recently I’ve been thinking about the art of data movement. What are some of the most important pieces that a data engineer needs to think about when confronted with data ingestion? There is of course data exporting as well, and in that case, […]
2022-11-11
6,072 reads
2022-11-07
383 reads
Migrate the SSIS Catalog in Just a Few Clicks
This wizard migrates SSIS Catalog from one server to another in just a few clicks.
2022-10-27 (first published: 2021-08-17)
16,593 reads
Assert Transformations in Azure Data Factory
This article will show how you can use Azure Data Factory to check your data quality with an assertion.
2022-11-02 (first published: 2022-10-24)
4,152 reads
Azure Data Factory Interview Questions and Answers
Get a few common questions and possible answers about Azure Data Factory that you may encounter in an interview.
2022-06-03
4,470 reads
The Script Activity in Azure Data Factory
Learn about using the Script activity in Azure Data Factory to run DDL or DML statements.
2022-05-13
19,529 reads
Blogs
Optimising Costs: Strategies for Efficient Cloud Resource Management
By HeyMo0sh
Over time, I’ve realised that one of the hardest parts of cloud management isn’t...
Cost Visibility: Tracking and Analysing Your Cloud Spend
By HeyMo0sh
One of the biggest challenges I’ve faced in cloud operations is maintaining clear visibility...
Whiling away an afternoon, thinking
By Steve Jones
I come to Heathrow often. Today is likely somewhere close to 60 trips to...
Forums
Fun with JSON II
Comments posted to this topic are about the item Fun with JSON II
Changing Data Types
Comments posted to this topic are about the item Changing Data Types
Answering Questions On Dropped Columns
Comments posted to this topic are about the item Answering Questions On Dropped Columns
Question of the Day
Fun with JSON II
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