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Day: July 21, 2022

Sorting in KQL

Robert Cain continues a series on KQL:

Like most query languages, the Kusto Query Language as the ability to sort the output. It works almost, but not quite, like you expect. So let’s take a look at the KQL sort operator.

Read on to get the general idea but also some of the nuance behind this operator.

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The Benefit of Tick Marks on a Visual

Alex Velez lays out the case for tick marks:

Lately, I’ve noticed that more and more graphs don’t include gridlines. If it’s unclear, I believe this to be a positive trend. I, myself, rarely use gridlines, and often remove them when I find them in a graph I’m reviewing. But I don’t stop there. 

More often than not, if a chart has gridlines, it will be lacking tick marks along the axis, and possibly an axis line as well. 

Read on to see why.

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Storing sp_BlitzIndex Details between Reboots

Tracy Boggiano continues a series on starting a new job as a DBA:

I mentioned in my New Database Job – The 90 Day Plan blog how I have a trick for storing index usage stats up until close to the next reboot of the SQL Server.  You really can do this for any DMV related query that you gets reset at the reboot of a SQL Server instance.  With this I am able to have data of the most the current index usage stats up to the midnight before a reboot of my SQL instances to analyze.

This is a good one to store, as is the output of sp_WhoIsActive.

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Azure SQL Database and the Well-Architected Framework

Jason Bouska has a big announcement:

Microsoft Azure SQL Database is a fully managed cloud database (PaaS) that handles many database management tasks without user intervention. Tasks such as patching, upgrading, taking backups, and monitoring can be configured to the specific needs of the workload and are performed in the background. Azure SQL Database runs the latest stable version of SQL Server and patched OS with 99.99% availability. The intelligent automated functions built into the database free up the user to focus on other important tasks.

Today I am introducing the Azure Well-Architected Service Guide for Azure SQL Database. Like other service guides, this guide for Azure SQL Database contains design considerations, checklists, and detailed configuration recommendations that can assist cloud architects in deploying optimal Azure SQL workloads in line with the guiding tenets of the Well-Architected Framework: security, reliability, cost management, performance efficiency, and operational excellence.

I’ve found that the Well-Architected Framework (whose overloaded acronym is still annoying) works best once you’re far enough along that you have a good idea of workload characteristics, meaning it’s not for the pre-planning state. Also, a full review might take hours or days and require several people to complete, not just a DBA.

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Verifying a Database Backup Has Occurred

Lee Markum reviews backup logs:

As data professionals responsible for SQL Server, it is drilled into our heads that we need to take backups. But, how do we know we actually have backups available to us when we need them? How can we verify that a backup has been taken? Some types of auditing that an employer has to undergo might require proof of backups. How will you provide it?

Read on for three options. Note that this post is about finding the existence of backups, not checking to see if the backups are any good.

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Errors Sending Subscription E-mails in SSRS

Garry Bargsley sorts out an e-mail problem:

Recently, I was tasked with creating an email subscription to a new SSRS report in an environment that I was not familiar with.  I have created my fair share of subscriptions in my day, and this one was very straightforward.

I found the report, clicked on Manage, and went to the Subscription page.  Clicked on New Subscription and filled in all the information, easy peasy.

The subscription is ready to go when the schedule kicks in the next day, or so I thought.

Turns out that wasn’t quite the case. Read on to see what happened and how Garry fixed the problem.

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The Basics of Slowly Changing Dimensions

Soheil Bakhshi explains what slowly changing dimensions are:

Another example is when a customer’s address changes in a sales system. Again, the customer is the same, but their address is now different. From a data warehousing standpoint, we have different options to deal with the data depending on the business requirements, leading us to different types of SDCs. It is crucial to note that the data changes in the transactional source systems (in our examples, the HR system or a sales system). We move and transform the data from the transactional systems via extract, transform, and load (ETL) processes and land it in a data warehouse, where the SCD concept kicks in. SCD is about how changes in the source systems reflect the data in the data warehouse. These kinds of changes in the source system do not happen very often hence the term slowly changing. Many SCD types have been developed over the years, which is out of the scope of this post, but for your reference, we cover the first three types as follows.

Click through for depictions of the first three types as well as implementation details and pains.

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