A graph database is a type of NoSQL database that is based on graph theory. Graph databases are ideal for storing data that has complex many to many relationships. In this article, we will study the very basics of graph databases with the help of a simple example.
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This article gives a walk-through of SQL Server Statistics and different methods to perform SQL Server Update Statistics.
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It is essential for the DBA to need to ensure the SQL Server database performance. Performance tuning is an open-ended task, and you need to ensure the monitoring of various database parameters.
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In this article, we’re going through many of the tools we can use for monitoring SQL Server performance. SQL Server is chock-full of lots of good reports that allow 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.
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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In the previous articles, we discussed several ways of taking backup and testing the restore process to ensure the integrity of the backup file.
In this article, we’re going to discuss the importance of the database backup reporting. This kind of reporting will be designed to eliminate any unnecessary risk that may arise with the safety and security of information. This is the reason, the high-level report; Daily Health Check report will be generated and sent to the SME or to the DBA responsible for IT Infra management.
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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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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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R is a very popular data programing language. R is especially used in data analysis, statistics calculations, predictions, data mining and machine learning. R is used by data scientist, economist, genetic scientists, and statisticians. R has very wide usage in real life. Healthcare, finance, marketing, and manufacturing are some of them.
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Understanding indexing needs allows us to ensure that important processes run efficiently and that our server hardware is not being over-taxed by poorly performing queries.
Collecting metrics on SQL Server index usage and missing index needs is critical to making smart decisions. To be truly proactive, though, we need to create a framework that allows us to quickly, efficiently, and regularly report on changes in indexing needs. With a system in place that can let us know when changes are needed, we can stay ahead of the optimization game and keep our customers happy!
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In the previous article entitled “What are SQL Server deadlocks and how to monitor them“, we’ve seen how a deadlock can occur and which tools are available to DBA or developer to get simple or extended information about the conditions that lead a particular deadlock situation to occur.
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Once collected, job performance metrics can be used for a variety of reporting needs, from locating jobs that are not performing well to finding optimal release windows, scheduling maintenance, or trending over time. These techniques allow us to maintain insight into parts of SQL Server that are often not monitored enough and prevent job-related emergencies before they become emergencies.
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Basic extraction of the SQL Server database data is usually achieved by querying the databases and creating stored procedure to automate the extraction process. Unfortunately, extracting the information in this way will not yield high-end reports, and only basic table-shaped reports are available when extracting the information via SQL Server Management Studio or similar tools. In order to create high-end reports that will include additional projections of the data, such are graphs, lists, charts… SQL Server offers powerful reporting options within the SQL Server Reporting service.
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Let me preface this post by saying that this was a process that evolved over time. It started as a simple sql statement that emailed me a csv file. From there the actual SQL code evolved to display cleaner results. When I learned what powershell could do, I spent some time learning it during my lunch breaks at work. Even when I implemented a powershell script for the first time, it still wasn’t a clean looking report, but it was still better than what we had prior. Even now there is room for improvement but I am happy with the results and hope that it can provide some help to other SQL DBA’s out there.
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In this new article, we will create a SQL Server Report using SQL Server Reporting Services from a SQL Server machine installed in an Azure Virtual Machine. We will show step by step how to connect from a local machine to a VM Azure Database and generate a SQL report.
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Now that Karla’s restore process is mature, it is time to pre-stage the means of reporting on these events. Two major actions have been taken for each database tested. First a restore operation occurred. The restore operation validates that the backup file is well formed and that there is nothing wrong with the data which would cause a failure. Next CheckTables was executed to thoroughly inspect for data corruption and any consistency errors. Each of these two actions will have their own methods of providing evidence of successful completion. Recall the requirements set by Karla, in part 1 of this series, for the reporting piece. Read more »
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