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Resolving and Preventing Deadlocks in SQL Server

Deadlocks in SQL Server can be frustrating and can cause significant performance and reliability issues. A deadlock occurs when two or more transactions are waiting for each other to release a lock on a resource, resulting in a situation where no transaction can proceed, and eventually, one of them is automatically killed and rolled back. This can happen when two transactions try to access the same data in a different order or when one transaction holds a lock on a resource while waiting for a lock held by another transaction. In this blog post, we’ll discuss how to troubleshoot and prevent deadlocks in SQL Server.

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Incremental Integrity Check for Large Databases

Traditional database integrity checks in SQL Server can be time-consuming and resource-intensive, especially for large databases, even when using super cool tools like Ola Hallengren’s maintenance solution.

To address this challenge, I developed a TSQL script for performing incremental integrity checks, which significantly optimizes the process and reduces its impact on the server.

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SQL Server Index Mastery: Choosing the Right Column Order

It’s been a while since my last post about SQL Server performance optimization. This one focuses on index design and how the order of columns in your indexes can make or break your database queries. Using my insights from real-world consulting experience, this guide should help you understand the critical decisions that would impact your database performance.

How does SQL Server decide where to look first when executing a query? The answer lies in the structure of your indexes. Learn how the sequence of key columns can optimize your data retrieval, making your database faster and more responsive.

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We need to talk about the elephant in the room – the future of DBAs

Hey there, pull up a chair, and let’s have a real heart-to-heart about what we all know has been happening this past decade in the world of DBAs. Yeah, I know, not exactly what you were looking for in my mostly technical blog, but stick with me here because this talk we’re going to have… Is very, very important.

You see, in this past decade or so, we’ve all noticed a trend where more and more businesses are looking for DBAs who know a bit about everything: RDBMS, NoSQL, Key-Value databases, Cache Databases, Full-Text Search Databases, Vector Databases, and more. In response, more and more data professionals prefer to become multi-disciplinary, doing a bit of everything… Even if it means becoming a part-time Data Engineer / Data Analyst / Data Scientist / DevOps / whatever. Otherwise, they fear that they won’t be able to find enough job opportunities.

But, there’s a cost to that approach. Sometimes a very high cost.

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