In previous article Build a Google BigQuery Resource, we saw how to build a BigQuery resource, and then build a Google OAuth refresh token. In Part Two here, we’ll build an Azure SQL data resource, and then build, configure, and test the Azure Data Factory that will link the cloud resources we built.
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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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Azure Data Studio (ADS) is a popular cross-platform (Windows, Linux) tool for database professionals. It provides various useful features such as T-SQL editor, Visualizations, insights, Peek definitions, Notebooks, Git integration, extensions and more. Extensions add new functionality in the ADS. Microsoft provides several useful extensions. We have already covered few useful extensions in the Azure Data Studio category on SQLShack.
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This article gives an insight into the terms in the Git repository of Azure Data Studio. In the previous articles, we learned the following things:
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In the last article, Source Control using Git in Azure Data Studio (ADS), we explored the following topics:
In this article, we will take a step forward and integrate Git installed locally on the GitHub.
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Azure Data Studio is a tool for both developers and database administrators with exciting features. You can install ADS on both Windows and Linux platforms. You can go through various Azure Data Studio articles on SQLShack to be comfortable with the tool and its features.
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Azure Data Studio extensions enable adding new functionality for development and administrative tasks. It is an open-source functionality and allows Microsoft as well as third party extensions using Marketplace. We explored a few useful extensions in the Azure Data Studio category of articles.
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In the previous articles listed below, we went through the Azure Data Studio tool, starting from the installation procedure, showing the purpose of each component, how to organize your connections, and develop the different types of SQL Server database objects using the interactive query editor in that data studio.
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In the previous two articles, Starting your journey with Azure Data Studio and Developing your SQL Server database using Azure Data Studio, we introduced the Azure Data Studio tool by describing the main components of that data studio and showed how we can take advantages from it in developing and organizing the database related projects.
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In the previous article, Starting your journey with Azure Data Studio, we put the first stone that helps you to be familiar with the Azure Data Studio and start using it to interact with your database objects.
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In this article, we will introduce the Azure Data Studio in a way that makes it easy for you to start using it. Enjoy the reading!
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Azure Data Studio (ADS) is an integrated, lightweight database development for supporting both on-premises and cloud databases. It can be installed on Windows as well as Linux operating system. I am assuming you are familiar with the SQL Server Management Studio. If you work on Linux based SQL Server instance, you can install only ADS in those systems. We can use integrated terminals to execute the PowerShell and Terminal sessions for the Linux system.
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In this article, we will explore charts in an Azure Data Studio using data stored in SQL Server tables.
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This article gives an overview of viewing execution plans in the Azure Data Studio.
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SQL Notebooks are an interactive way of creating documents, executing T-SQL queries along with Python and PowerShell codes. It is available in Azure Data Studio, a cross-platform client tool that works on both Windows and Linux operating systems.
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Microsoft supports SQL Notebooks in Azure Data Studio. It is an exciting feature that allows creating a notebook for multiple languages such as Python, SQL, PowerShell. You might have heard about the Jupyter notebook. It is a popular web-based notebook that provides rich programming language support. SQL Notebook is an inspiration for the Jupyter notebook.
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The Jupyter notebook is a powerful and interactive tool that supports various programming languages such as Python, R, Julia. This open-source utility is popular among data scientists and engineers. This notebook integrates both code and text in a document that allows you to execute code, view visualization, solve mathematical equations.
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This article installs PostgreSQL on Ubuntu 16.4 operating system and connects the database using Azure Data Studio.
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This article explores different ways to generate data scripts using Azure Data Studio and SQL Server Management Studio.
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This article explores the Python scripts for encrypting and decrypting passwords in SQL Server using Azure Data Studio SQL Notebooks.
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This article explores the Python SQL scripts in SQL Notebook of Azure Data Studio.
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Azure Data Studio provides a modern and productive experience for managing on-premise and cloud-based SQL Server instances. Previously, we discussed many useful features of it, and you can explore these articles in Azure Data Studio category.
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This article explores the SQL Server Schema Compare extension in the Azure Data Studio.
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Azure Data Studio is an open-source, cross-platform and lightweight data management tool. We can use it for on-premise SQL Server, Azure SQL database and Azure SQL data warehouse. Previously we knew this tool as SQL Operations Studio.
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This article prepares a handy SQL Notebook for DBAs. You can use this notebook to troubleshoot performance issues and for getting SQL Server instance details.
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