Takeaways from Data Grillen 2024
Two days of Data, Beer and Bratwurst. What did it bring me, find out by reading this photo-rich article.
Two days of Data, Beer and Bratwurst. What did it bring me, find out by reading this photo-rich article.
Steve has had a good time sharing knowledge with others at events. He gives you a few thoughts on why you might join him at a future event.
Over the past years, “traditional” ETL development has morphed into data engineering, which has a more disciplined software engineering approach. One of the benefits of having a more code-based approach in data pipelines is that it has become easier to build metadata driven pipelines.
Learn how to use the OneLake Explorer and Data Wrangler extension in VS Code to empower users to work with data in Microsoft Fabric.
Steve has a few thoughts on invisible downtime, a term he had never heard until recently.
We experienced several unplanned outages and failovers on our SQL Server Always On Availability Groups. We want to know the root cause to prevent them from happening in the future. How do we identify the root causes of unplanned Availability Group outages and failovers?
This article includes an overview of how big data and Artificial Intelligence (AI) models work together.
Steve has a few thoughts on Kubernetes and how much data professionals should care about the technology.
The first two articles in this series demonstrated how PostgreSQL is a capable tool for ELT – taking raw input and transforming it into usable data for querying and analyzing. We used sample data from the Advent of Code 2023 to demonstrate some of the ELT techniques in PostgreSQL.
Or for short, “Why you have to play the game” “Don't tell me the odds”, cried out Han Solo just before doing something that seemed impossible. How on Coruscant did he do that? Well, as a certain director said about a certain floating door in a galaxy we all call home. ”It was in the […]
By HeyMo0sh
Over time, I’ve realised that one of the hardest parts of cloud management isn’t...
By HeyMo0sh
One of the biggest challenges I’ve faced in cloud operations is maintaining clear visibility...
By Steve Jones
I come to Heathrow often. Today is likely somewhere close to 60 trips to...
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