Hands-on Azure Data Studio
Hands-on Azure Data Studio
About the Book
This book introduces Microsoft Azure Data Studio and shows how anyone working with data -- Database Developers, Data Analysts, Data Scientists, Database Administrators, and Software Developers -- can use Azure Data Studio to dramatically streamline and accelerate their daily work. Learn to connect to databases whether in the Azure cloud or hosted on premises in your corporate environment. You can even connect to databases from competing brands and from the world of open source. Then learn how you can query and analyze data using a fusion of languages such as Python, SQL, and PowerShell neatly wrapped in Jupyter Notebooks.
Azure Data Studio is a quickly emerging software platform from Microsoft meant to be a free-form toolbox for all sorts of data manipulation and analytics tasks. Going beyond just querying interactively, this book shows how you can maximize your work products, whether it’s a small code snippet, or an exhaustive notebook. You’ll learn how to benefit from Git and GitHub where your queries and analysis can be shared and improved by others in your organization, or perhaps collaborate with those on the outside. If you’re involved in a role working with data and you are looking for an open architecture platform for exploring your data, managing your data, and for collaborating with colleagues to derive business value by analyzing that data, then this is the book you'll want to read!
About the Author
Table of Contents
-
Introduction
- Who this book was written for
- What you need to get the most from this book
-
Source Code and Notebook Samples
- Companion Database
- About the Author
- Why this book
-
Chapter 1 - Open Source, Cross-Platform, Multi-Database
-
What “Open Source” means for this new breed of Microsoft Software
- A perspective on Open Source
- Extend and Enhance ADS
- Contribute to ADS
-
The new options provided by “Cross-Platform” computing
- What about the Database ‘Platform’
- What “Multi-Database” means for your SQL experience
- What about ‘Management Studio’?
- Opening Azure Data Studio
-
What “Open Source” means for this new breed of Microsoft Software
-
Chapter 2 - Everything Starts with a Connection
-
Creating, Using, and Managing Connections
- Connecting to SQL Server
- Connecting to Azure SQL Database
- Azure Container in ADS
- Connecting to PostgreSQL
-
Grouping and Color Coding your Connections
- Color Coding Groups
-
Central Management Servers Extension
- Summary
-
Creating, Using, and Managing Connections
-
Chapter 3 - SQL Editing Reimagined
-
IntelliSense, Snippets and Object Definitions
- Code Snippets
- Object Definitions
- Creating a Snippet for Column Definitions
- Saving Queries and Snippets
- Top Down View with Minimap
- SQL Queries via the Command Terminal
-
IntelliSense, Snippets and Object Definitions
-
Chapter 4 - Visualizing and Exporting Your Queries
- Loading Sample Data
- Anatomy of the Results Pane
- Querying for Easy Visuals
- Getting Pixel Perfect
-
Chapter 5 - Getting Things Done with Notebooks
-
Notebook Building Blocks
- Comments on Steroids via Markdown
- Fun with Code Cells
- Story with a SQL Notebook
-
Kernel Options
- Simple PowerShell Notebook
- Simple Python Notebook
- More to Come
-
Notebook Building Blocks
-
Chapter 6 - Reaching Beyond SQL with PowerShell, the Terminal Window, and an Extension
-
Creating a Simple Dataflow
- Dataflow Components
- Getting Started
- Specifying the ‘Source’ Table
- Creating the ‘Destination’ Table
- Running the PowerShell Script in a Notebook
- Running the PowerShell Script in the Terminal
- Using the “Simple DataFlow” Extension for ADS
-
Creating a Simple Dataflow
-
Chapter 7 - Source Control by Design
- Cloning this book’s repository
- Creating your own repository
- Using Git to Manage File Changes
- Publishing your ADS repository to GitHub
-
Chapter 8 - Free and Easy Extensions
- Installing and Managing your Extensions
- SQL Server Schema Compare
-
Simple Data Scripter
- Extension Wrap-up
- Conclusion
-
Appendix A - Understanding the car_crash DataMart
-
- Sample Data
-
- Notes
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