In this article we are going to show how to get started with the Azure SQL Database auditing using specific auditing techniques to configure audit specification and reconstruct audit data trail. Companies nowadays choose to migrate to the Azure cloud platform due to multiple reasons like:
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SQL Server creates an optimized execution plan based on the available inputs such as statistics, indexes. By default, it chooses a cost-optimized execution plan and executes the query. Sometimes, we use SQL queries table hints to override the default mechanism. Developers popularly use WITH (NOLOCK) query hint in a Select statement to avoid blocking issues.
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We can rely on Azure SQL to build reliable, high-quality relational database solutions. In the cloud, Google offers BigQuery as a big data product that has large data capacities, and a standard SQL syntax. Although it can handle data manipulation, it works better as a data warehouse product because of certain product limitations. If we can integrate these products, they become even more useful. This two-part article will show how to link these products together. Part one here will show how to build a BigQuery resource, and then build a Google OAuth refresh token, or security key. Part two will show how to set up an Azure SQL data resource, and build, configure, and test the Azure Data Factory that will link those resources.
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In this 35th article in SQL Server Always On Availability Groups, we will implement a custom policy for monitoring AG groups.
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In this article, we will learn an approach to source data from AWS Redshift and populate it in the Azure SQL database, where this data can be used with other data on the SQL Server for desired purposes.
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This article talks about multiple ways to install tSQLt for SQL unit testing database projects managed through SQL Server Data Tools (SSDT).
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In the previous articles, we showed how to copy data between different data stores, located in an on-premises server or in the cloud and how to perform data transformation on that data using the Azure Data Factory.
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In this 34th article on SQL Server Always On Availability Groups, we will explore policy-based management features for the AG’s.
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In this article, you will learn about writing a playbook with Ansible to provision the Azure SQL database. In addition, you will also learn about Ansible and its design constructs and concepts.
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In this article, you will learn how to export data from Azure SQL Database to Azure Data Lake Storage using Azure Data Factory.
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In the previous articles, Copy data between Azure data stores using Azure Data Factory and Copy data from On-premises data store to an Azure data store using Azure Data Factory, we saw how we can use the Azure Data Factory to copy data between different data stores located in an on-premises machine or in the cloud.
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In this article, we will explore User-defined SQL Server Types and their usage.
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SQL Injection is a well-known technique used to attack SQL-based applications. In this article, we’ll focus on examples showing how you could exploit database vulnerabilities using this technique, while in the next article we’ll talk about ways how you can protect your application from such attacks.
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After discussing Regression in the previous article, let us discuss the techniques for Classification in Azure Machine learning in this article. Like regression, classification is also the common prediction technique that is being used in many organizations. Before the regression we have discussed basic cleaning techniques, feature selection techniques and Principal component analysis in previous articles, now we will be looking at data classification techniques in azure machine learning in this article.
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In this article, I am going to show how we can automate the report of unused database files using T-SQL.
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In the previous article, Copy data between Azure data stores using Azure Data Factory, we discussed how to copy the data stored in an Azure Blob Storage container to an Azure SQL Database table using Azure Data Factory and review the created pipeline components and result.
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In this article, we will uncover some secrets about the SQL Server tempdb database. Tempdb is a system database and it is used for various internal and user operations. Besides this, the tempdb has many unique characteristics, unlike the other databases. When we take into account all of these features of the tempdb, there is no doubt that it is an essential part of the SQL Server.
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In the previous article, Starting your journey with Microsoft Azure Data Factory, we discussed the main concept of the Azure Data Factory, described the Data Factory components and showed how to create a new Data Factory step by step.
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This article discusses useful considerations for SQL Server Disaster Recovery.
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In this article, we will explore, how we can increase SQL Server performance with the help of the wait statistics. Wait statistics are one of the most important indicators to identify performance issues in SQL Server. When we want to troubleshoot any performance issue, at first we need to diagnose the problem correctly because correctly diagnosing problems help with half of the solution. Now, let’s learn wait statistics which helps to identify performance issues properly.
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In this article, we will install and configure SQL Server Linux (2017 version) on SUSE Linux in the Amazon EC2 Instance.
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In this article, I am going to show how we can automate a database daily health report using T-SQL scripts. For a senior database administrator, it is always important to review the health of the database server. When a DBA manages many database servers, it becomes difficult to visit every server and review the status of databases, SQL jobs, and backups. To ease the monitoring, I have developed a T-SQL script that populates the following information:
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Working as an Azure Data Engineer, you are responsible for designing and implementing Azure data platform solutions in which you need to choose the best method to ingest structured, semi-structured and unstructured data that are generated from various data sources, in order to be processed in batches or in real-time by the applications and stored or visualized as per the project requirements.
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Data consistency errors are the nightmares of database administrators (DBAs) and when we notice “Could not continue scan with NOLOCK due to data movement” explanation in any error message, we are sure of getting in trouble. In this article, we will discuss the details of this data consistency problem.
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The recent trend proves that the adoption of the Cloud has much greater significance and importance in modernizing IT. If you are working on migrating the on-premises SQL Server to Microsoft Azure cloud, you need to have a better understanding of the key differences between Azure SQL databases and SQL Server on Azure VMs and options that work best for you.
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