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How To Use Regular Expressions for Data Validation and Cleanup

You need to provide data validation at the server level for complex strings like phone numbers, email addresses, etc. You may also need to do data cleanup / standardization before moving it from source to target. Although SQL Server provides a fair number of string functions, the code developed with these built-in functions can become complex and hard to maintain or reuse.

2011-03-03

15,100 reads

External Article

How to reduce MDX code redundancy in SQL Server Analysis Services (SSAS)

To query an Analysis Services cube, MDX is used as the query language. In most business settings, one would find a set of queries that are common across a number of user query requirements. To cater to this, even with a modest size IT team, there is a good chance that the same queries are developed redundantly either within a SSAS MDX script or repetitively in an ad-hoc manner in client applications. In this tip we would look at how to reuse queries without redeveloping them over and over.

2011-03-01

3,774 reads

External Article

Retrieving SQL Server Fixed Database Roles for Disaster Recovery

We ran into a case recently where we had the logins and users scripted out on my SQL Server instances, but we didn't have the fixed database roles for a critical database. As a result, our recovery efforts were only partially successful. We ended up trying to figure out what the database role memberships were for that database we recovered but we'd like not to be in that situation again. Is there an easy way to do this?

2011-02-23

3,104 reads

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Fun with JSON II

By Steve Jones - SSC Editor

Comments posted to this topic are about the item Fun with JSON II

Changing Data Types

By Steve Jones - SSC Editor

Comments posted to this topic are about the item Changing Data Types

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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