Write Cleaner T-SQL Using Version Control
If we only use version control as a way to back up our code then it is pure overhead but actually there are real benefits. We can use source control to write better, cleaner, more readable code.
Power Query Formula Language in Power BI Desktop
The Power Query Formula Language (PQFL) is a functional language that drives the Power BI transformations, and allows you to create mashup queries from scratch. In this article, Rob Sheldon demonstrates how to use it in Power BI Desktop to extract data from its source, filter rows, specify the columns, clean the data, and create visualisations.
SQL Server Stored Procedures and SET options
SET options on stored Procedures work a bit different when compared with ad-hoc queries. These differences in behavior are often overlooked when developing the procedures and generating deployment scripts. This mistake can lead to undesired behavior in the application.
How to Avoid Conditional JOINs in T-SQL
Relational databases go out of their way to execute SQL, however bad the crimes against Codd and relational theory within the query might be. The 'conditional join' can be executed, but at great cost. As always, it is much better to sit back and restate the problem in a set-based way - Dwain Camps explains.
Creating Dashboards for Mobile Devices with Datazen
In this fourth installment, Arshad Ali demonstrates creating filters, publishing dashboards to the Datazen server and creating drill-through dashboards.
Install SQL Server Management Studio with Web Installer without Internet Access
One of the new features of SQL Server 2016 is the introduction of a Web Installer for the client tools. In this article, Daniel Farina goes through the entire process of downloading and installing the client tools even on machines without internet access.
Learning the Query Store
Links and references to understand what the Query Store is in SQL Server 2016.
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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
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