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Viktor Suha

Azure Data Studio is a lightweight, open source, cross-platform client tool that enables you to connect to a database and work with the data. This course will teach you how to use Azure Data Studio to get the data you want.

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Azure Data Studio is a lightweight, open source, cross-platform client tool that enables you to connect to a database and work with the data. This course will teach you how to use Azure Data Studio to get the data you want.

Getting data and working with data from an ever increasing number of data sources have become paramount for the developer. In this course, Data Literacy: Essentials of Azure Data Studio, you’ll learn how to connect to different databases, both on-premises and in the cloud, then run your SQL queries from a lightweight, cross-platform and open source client tool called Azure Data Studio. First, you’ll explore what Azure Data Studio is, what capabilities it has, what you can use it for, and how it compares to SQL Server Management Studio. Next, you’ll discover how to download and install this tool to start working with your data. Finally, you’ll learn what the differences between Data Manipulation Language and Data Definition Language SQL statements are, how to run your SQL queries, how to manage database connections to SQL Server, Azure SQL Database or PostgreSQL, and what notebooks are. When you’re finished with this course, you’ll have the skills and knowledge of using Azure Data Studio to query and work with your data from different data sources.

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What's inside

Syllabus

Course Overview
Understanding Azure Data Studio
Querying Data with Azure Data Studio

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Teaches how to connect to databases and run SQL queries, which are core skills for working with data
Taught by Viktor Suha, an instructor who is recognized for expertise in data-centric topics
Suitable for beginners who are interested in learning the basics of working with data using Azure Data Studio
Emphasizes the use of a lightweight, open source tool that is widely used in industry
Covers both on-premises and cloud-based databases, making it relevant for a variety of work environments

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Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Data Literacy : Essentials of Azure Data Studio with these activities:
Organize Azure Data Studio notes and resources
Organizing your Azure Data Studio notes and resources will help you stay organized and make it easier to find the information you need when you need it.
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  • Gather your Azure Data Studio notes and resources.
  • Create a system for organizing your notes and resources.
  • Organize your notes and resources according to your system.
Review SQL Server Management Studio
Reviewing SQL Server Management Studio will help you identify its limitations and prepare you to learn the advantages of Azure Data Studio.
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  • Identify the features of SQL Server Management Studio.
  • Review the documentation for SQL Server Management Studio.
Follow Azure Data Studio tutorials
Following tutorials will help you get up and running quickly with Azure Data Studio and become familiar with its interface and capabilities.
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  • Find Azure Data Studio tutorials online.
  • Follow the steps in the tutorials.
  • Experiment with the features of Azure Data Studio.
Four other activities
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Create and run SQL queries in Azure Data Studio
Practicing writing and running SQL queries will help you develop proficiency in using Azure Data Studio and solidify your understanding of SQL syntax.
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Show steps
  • Connect to a database using Azure Data Studio.
  • Create a new SQL query.
  • Write a SQL query to retrieve data from a table.
  • Run the SQL query.
  • Examine the results of the SQL query.
Attend an Azure Data Studio workshop
Attending an Azure Data Studio workshop will provide you with an opportunity to learn from experts and ask questions about the tool.
Browse courses on Azure Data Studio
Show steps
  • Find an Azure Data Studio workshop.
  • Register for the workshop.
  • Attend the workshop.
Contribute to the Azure Data Studio open source project
Contributing to the Azure Data Studio open source project will help you deepen your understanding of the tool and its underlying architecture.
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  • Find an issue to work on.
  • Fork the Azure Data Studio repository.
  • Make changes to the code.
  • Create a pull request.
Contribute to a Docker container for Azure Data Studio extension
Contributing to a Docker container for Azure Data Studio extension will help you gain practical experience in extending the functionality of the tool.
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Show steps
  • Find a Docker container for Azure Data Studio extension to contribute to.
  • Fork the repository.
  • Make changes to the code.
  • Create a pull request.

Career center

Learners who complete Data Literacy : Essentials of Azure Data Studio will develop knowledge and skills that may be useful to these careers:
Database Administrator
Database Administrators set up, configure, and maintain databases, often in cloud environments. With training in Azure Data Studio, one would be able to work with data from a variety of data sources. This course may be particularly useful for a Database Administrator who needs to connect to disparate databases from a single tool.
Data Analyst
Data Analysts discover actionable insights from large datasets to help businesses make better decisions. While not required, training in Azure Data Studio may help a Data Analyst pull data from both on-premises and cloud data sources, and write SQL queries to manipulate and analyze the data in order to quickly derive the insights that drive business decisions.
Business Analyst
Business Analysts identify business needs and develop solutions through data analysis and modeling. Training in Azure Data Studio may be useful for a Business Analyst who needs to work with data from a variety of sources to derive insights for stakeholders across an organization.
Data Engineer
Data Engineers design, build, and maintain data pipelines to ensure data quality and availability. While not required, knowledge of Azure Data Studio may be helpful for a Data Engineer tasked with pulling data from a variety of on-premises and cloud-based data sources.
Data Scientist
Data Scientists build and apply predictive models to large datasets to uncover patterns and trends. While not required, training in Azure Data Studio may be helpful for a Data Scientist who wishes to work with data from both on-premises and cloud data sources to build models.
Software Engineer
Software Engineers design, build, and maintain software applications. While not required, training in Azure Data Studio may be useful for a Software Engineer tasked with working with or building features such as data dashboards or reporting functions.
Systems Engineer
Systems Engineers work with customers to design and implement technological solutions. Knowledge of Azure Data Studio may be helpful for Systems Engineers tasked with working with customers who need to connect to data sources and run SQL queries from a single tool.
Information Security Analyst
Information Security Analysts protect an organization's data and computer systems from cyber threats. Training in Azure Data Studio may be useful for an Information Security Analyst tasked with maintaining database security.
Database Developer
Database Developers design and create databases to meet an organization's needs. Training in Azure Data Studio may be helpful for a Database Developer who needs to connect to both on-premises and cloud-based databases to design and implement database solutions.
Data Architect
Data Architects design and manage an organization's data architecture. Training in Azure Data Studio may be helpful for a Data Architect who needs to manage data across a variety of data sources.
Project Manager
Project Managers plan and execute projects to achieve specific goals. Training in Azure Data Studio may be helpful for a Project Manager who needs to work with data from a variety of sources to track project progress and make decisions.
Data Governance Analyst
Data Governance Analysts ensure that an organization's data is used in a consistent and ethical manner. Training in Azure Data Studio may be helpful for a Data Governance Analyst who needs to track and manage data from a variety of sources to ensure compliance with internal and external regulations.
IT Auditor
IT Auditors evaluate and report on the effectiveness of an organization's IT systems and processes. Training in Azure Data Studio may be helpful for an IT Auditor who needs to review and assess database security and compliance.
Technical Writer
Technical Writers create documentation and other materials to help users understand and use software and technology products. While not required, training in Azure Data Studio may be helpful for a Technical Writer who needs to document how to use the tool to connect to databases and run SQL queries.
Quality Assurance Analyst
Quality Assurance Analysts test software products to ensure that they meet quality standards. While not required, training in Azure Data Studio may be helpful for a Quality Assurance Analyst who needs to test software that interacts with databases.

Reading list

We've selected seven books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Data Literacy : Essentials of Azure Data Studio.
A comprehensive guide to MongoDB, covering installation, configuration, data modeling, and querying. A valuable resource for both beginners and experienced users.
A comprehensive guide to Hadoop, covering installation, configuration, data processing, and analytics. A valuable resource for both beginners and experienced users.
A comprehensive guide to Spark, covering installation, configuration, data processing, and machine learning. A valuable resource for both beginners and experienced users.
A practical guide to deep learning with Python, covering neural networks, convolutional neural networks, and recurrent neural networks. A valuable resource for both beginners and experienced users.
A practical guide to natural language processing with Python, covering tokenization, stemming, lemmatization, parsing, and machine learning. A valuable resource for both beginners and experienced users.
A practical guide to artificial intelligence with Python, covering machine learning, deep learning, and natural language processing. A valuable resource for both beginners and experienced users.

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