Bojan Petrovic

How to collect performance and system information in SQL Server

August 16, 2018 by

In this article, we’re going to through many of the tools we can use for monitoring SQL Server. SQL Server is chock-full of lots of good reports that allows a DBA to quickly spot whether there is any current performance bottleneck on the SQL Server. Many of these sit on top of DMVs but they give us a visually interactive way to look and work with the data. We’re going to start with SQL Server Performance Dashboard Reports.

Dashboard Reports

Let’s jump into SQL Server Management Studio (SSMS) and the first thing we’re going to take you through out-of-the-box dashboard reports of all levels. They can be found by right-clicking the SQL Server instance in Object Explorer, and from the context menu, you’ll find Reports > Standard Reports:

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Ed Pollack

Reporting and alerting on job failure in SQL Server

March 12, 2018 by

SQL Server Agent can be used to run a wide variety of tasks within SQL Server. The built-in monitoring tools, though, are not well-suited for environments with many servers or many databases.

Removing reliance on default notifications and building our own processes can allow for greater flexibility, less alerting noise, and the ability to track failure conditions that are not typically tracked by SQL Server!


At the heart of the SQL Server Agent service is the ability to create, schedule, and customize jobs. These jobs can be given schedules that determine at what times of day a task should execute. Jobs can also be given triggers, such as a server restart or alert to respond to. Jobs can also be called via TSQL from anywhere that has the appropriate access and permissions to SQL Server Agent.

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Ed Pollack

How to quickly generate a large number of dimension tables for reporting applications

January 19, 2018 by


When building reporting structures, we typically have the need to build fact and dimension tables to support the apps that will consume this data. Sometimes we need to generate large numbers of dimension tables to support application needs, such as in Tableau, Entity Framework, or Power BI.

Creating this schema by hand is time-consuming and error-prone. Automating it can be a way to improve predictability, maintainability, and save a ton of time in the process!

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