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Kishan Iyer

This course delves into the use of the Databricks connect utility to link up local development environments such as Jupyter Notebooks or Pycharm and Azure Databricks. This allows you to develop Spark applications locally and run them on the cloud.

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This course delves into the use of the Databricks connect utility to link up local development environments such as Jupyter Notebooks or Pycharm and Azure Databricks. This allows you to develop Spark applications locally and run them on the cloud.

For any developer working with Databricks, it is important to make working with this technology as seamless as possible. In this course, Integrating Azure Databricks with Local Development Environments, you'll delve into different integrations which can be applied to enable development of Spark applications in your own local environments, but run the jobs we define on the Azure Databricks service in the cloud. First, you'll learn how to set up the Databricks connect utility, which creates a local environment that is linked to a cloud-hosted Databricks workspace. Next, you'll discover how to use the environment set up with Databricks connect to link a local Jupyter notebook with a workspace on the Azure cloud. Finally, you'll explore the Databricks connect environment, and enable the spawning of jobs from an application developed in the PyCharm IDE, then execute them on the Azure cloud. Once you complete this course, you will have the skills required to combine the convenience of building apps in your own development environment and the compute power of Azure Databricks to build robust and highly performant applications.

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What's inside

Syllabus

Course Overview
Setting up Databricks Connect
Connecting to Azure Databricks from a Local Jupyter Notebook
Connecting to Azure Databricks from PyCharm
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Good to know

Know what's good
, what to watch for
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Teaches Azure Databricks and Databricks connect utility, which are core tools for working with Big Data in the cloud

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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 Integrating Azure Databricks with Local Development Environments with these activities:
Review basic Apache Spark concepts and APIs
Reinforce foundational skills in Spark to enhance understanding of course materials.
Browse courses on Apache Spark
Show steps
  • Go through Spark documentation or tutorials.
  • Practice writing Spark code in a local environment.
Read through Azure Databricks documentation on connecting local environments
Gain theoretical knowledge on integrating local development environments with Azure Databricks.
Show steps
  • Visit the Azure Databricks website.
  • Locate and read through the documentation related to connecting local development environments.
Find a Databricks Connect Mentor
Connect with experienced Databricks Connect users who can provide guidance and support.
Show steps
  • Attend industry events and meetups to network with professionals.
  • Join online communities and forums dedicated to Databricks Connect.
  • Reach out to potential mentors through LinkedIn or email.
Nine other activities
Expand to see all activities and additional details
Show all 12 activities
Participate in an online forum or discussion group related to Azure Databricks and local development environments
Engage with peers to share knowledge, ask questions, and gain diverse perspectives on course-related topics.
Browse courses on Azure Databricks
Show steps
  • Find and join an online forum or discussion group.
  • Participate in discussions by sharing insights, asking questions, and responding to others.
Databricks Connect Tutorial
Follow a step-by-step tutorial to learn about the features and usage of Databricks Connect.
Show steps
  • Read the documentation and watch the official videos provided by Databricks.
  • Follow along with the hands-on exercises provided in the tutorial.
  • Join the Databricks community forums and ask questions if you encounter any difficulties.
Complete a set of Databricks connect exercises
Practice using the Databricks connect utility to improve understanding of local development environment integration.
Show steps
  • Set up the Databricks Connect utility in your local environment.
  • Connect to a workspace on Azure Databricks from a local Jupyter notebook.
  • Run a Spark job on Azure Databricks from PyCharm.
Databricks Connect Hands-on Exercises
Practice using Databricks Connect to link up local development environments with Azure Databricks.
Show steps
  • Set up Databricks Connect and link to your workspace.
  • Create a local Jupyter notebook and connect to your Azure Databricks workspace.
  • Create a local PyCharm application and connect to your Azure Databricks workspace.
  • Run Spark applications locally using Databricks Connect.
Databricks Connect Meetup
Attend or organize a meetup with other Databricks Connect users to share knowledge and collaborate.
Show steps
  • Find or create a local meetup group for Databricks Connect.
  • Attend meetups regularly and actively participate in discussions.
  • Organize a meetup and invite speakers or lead a session on Databricks Connect.
Databricks Connect Workshop
Attend or organize a workshop to learn more about the advanced features and use cases of Databricks Connect.
Show steps
  • Find or create a workshop dedicated to Databricks Connect.
  • Register for the workshop and prepare any necessary materials.
  • Actively participate in the workshop, ask questions, and share your experiences.
Build a Spark application that runs on Azure Databricks using the Databricks connect library
Apply knowledge of Databricks connect to create a functional Spark application with Azure Databricks integration.
Show steps
  • Set up a local development environment with Databricks connect.
  • Create a new Spark application in the local environment.
  • Configure the application to connect to Azure Databricks.
  • Run the application to perform data processing or analysis on Azure Databricks.
Databricks Connect Blog Post
Write a blog post or create a video tutorial sharing your knowledge and experience using Databricks Connect.
Show steps
  • Choose a specific topic or aspect of Databricks Connect to focus on.
  • Gather information and resources to support your content.
  • Create an outline or storyboard for your blog post or video.
  • Write or record your content, ensuring it is clear, concise, and engaging.
  • Proofread and publish your blog post or video tutorial.
Contribute to the Databricks Connect Open Source Project
Contribute to the open source development of Databricks Connect to enhance its features and capabilities.
Show steps
  • Review the Databricks Connect GitHub repository.
  • Identify areas where you can contribute or improve.
  • Fork the repository and create a branch for your changes.
  • Develop and test your contributions.
  • Submit a pull request with your changes and documentation.
  • Work with the Databricks Connect community to review and merge your contributions.

Career center

Learners who complete Integrating Azure Databricks with Local Development Environments will develop knowledge and skills that may be useful to these careers:
Database Administrator
Database Administrators (DBAs) are responsible for the day-to-day operation and maintenance of databases. They ensure that databases are running smoothly, data is secure, and backups are in place. The Integrating Azure Databricks with Local Development Environments course may be useful for aspiring Database Administrators because it teaches how to use Azure Databricks, a cloud-based data warehousing platform. This course can help Database Administrators learn how to use Azure Databricks to manage data, create data models, and perform data analysis.
Data Engineer
Data Engineers plan, build, test, and maintain data pipelines to manage the flow of data. They work closely with Data Analysts and Data Scientists to ensure that the data used for analysis is clean, accurate, and accessible. The Integrating Azure Databricks with Local Development Environments course may be useful for aspiring Data Engineers because it teaches how to use Azure Databricks, a cloud-based data engineering platform, to develop and execute Spark applications. This course can help Data Engineers learn how to use Azure Databricks to perform data transformations, data cleansing, and other data engineering tasks.
Software Engineer
Software Engineers design, develop, test, and maintain software applications. They work with a variety of programming languages and technologies to create software that meets the needs of users. The Integrating Azure Databricks with Local Development Environments course may be useful for aspiring Software Engineers because it teaches how to use Azure Databricks, a cloud-based data engineering platform. This course can help Software Engineers learn how to use Azure Databricks to develop and execute Spark applications, which can be used for a variety of data processing tasks.
Data Analyst
Data Analysts collect, clean, and analyze data to identify trends and patterns. They use this information to make recommendations and inform decision-making. The Integrating Azure Databricks with Local Development Environments course may be useful for aspiring Data Analysts because it teaches how to use Azure Databricks, a cloud-based data engineering platform. This course can help Data Analysts learn how to use Azure Databricks to perform data analysis tasks, such as data exploration, data visualization, and machine learning.
Data Scientist
Data Scientists use statistical and machine learning techniques to analyze data and extract insights. They work on a variety of projects, such as fraud detection, customer segmentation, and predictive analytics. The Integrating Azure Databricks with Local Development Environments course may be useful for aspiring Data Scientists because it teaches how to use Azure Databricks, a cloud-based data engineering platform. This course can help Data Scientists learn how to use Azure Databricks to perform data analysis tasks, such as data exploration, data visualization, and machine learning.
Business Analyst
Business Analysts work with stakeholders to understand their business needs and develop solutions to meet those needs. They may work on a variety of projects, such as process improvement, system implementation, and data analysis. The Integrating Azure Databricks with Local Development Environments course may be useful for aspiring Business Analysts because it teaches how to use Azure Databricks, a cloud-based data engineering platform. This course can help Business Analysts learn how to use Azure Databricks to analyze data and identify trends, which can be used to make better business decisions.
DevOps Engineer
DevOps Engineers work to bridge the gap between development and operations teams. They automate tasks and processes to improve the efficiency and reliability of software delivery. The Integrating Azure Databricks with Local Development Environments course may be useful for aspiring DevOps Engineers because it teaches how to use Azure Databricks, a cloud-based data engineering platform. This course can help DevOps Engineers learn how to use Azure Databricks to automate data engineering tasks and processes.
Cloud Architect
Cloud Architects design and implement cloud computing solutions. They work with clients to understand their business needs and develop cloud solutions that meet those needs. The Integrating Azure Databricks with Local Development Environments course may be useful for aspiring Cloud Architects because it teaches how to use Azure Databricks, a cloud-based data engineering platform. This course can help Cloud Architects learn how to use Azure Databricks to develop and implement cloud-based data solutions.
Systems Administrator
Systems Administrators are responsible for the day-to-day operation and maintenance of computer systems. They ensure that systems are running smoothly, data is secure, and backups are in place. The Integrating Azure Databricks with Local Development Environments course may be useful for aspiring Systems Administrators because it teaches how to use Azure Databricks, a cloud-based data engineering platform. This course can help Systems Administrators learn how to use Azure Databricks to manage data, create data models, and perform data analysis.
Project Manager
Project Managers plan, execute, and close projects. They work with a variety of stakeholders to ensure that projects are completed on time, within budget, and to the required quality standards. The Integrating Azure Databricks with Local Development Environments course may be useful for aspiring Project Managers because it teaches how to use Azure Databricks, a cloud-based data engineering platform. This course can help Project Managers learn how to use Azure Databricks to manage data engineering projects.
Security Analyst
Security Analysts work to protect computer systems and networks from unauthorized access, use, disclosure, disruption, modification, or destruction. They work with a variety of security tools and technologies to identify and mitigate security threats. The Integrating Azure Databricks with Local Development Environments course may be useful for aspiring Security Analysts because it teaches how to use Azure Databricks, a cloud-based data engineering platform. This course can help Security Analysts learn how to use Azure Databricks to analyze data and identify security threats.
Database Designer
Database Designers design and implement databases. They work with stakeholders to understand their data needs and develop databases that meet those needs. The Integrating Azure Databricks with Local Development Environments course may be useful for aspiring Database Designers because it teaches how to use Azure Databricks, a cloud-based data engineering platform. This course can help Database Designers learn how to use Azure Databricks to design and implement databases.
Data Architect
Data Architects design and implement data management solutions. They work with stakeholders to understand their data needs and develop data solutions that meet those needs. The Integrating Azure Databricks with Local Development Environments course may be useful for aspiring Data Architects because it teaches how to use Azure Databricks, a cloud-based data engineering platform. This course can help Data Architects learn how to use Azure Databricks to design and implement data management solutions.
IT Consultant
IT Consultants provide advice and guidance to clients on the use of information technology. They work with clients to assess their IT needs and develop solutions that meet those needs. The Integrating Azure Databricks with Local Development Environments course may be useful for aspiring IT Consultants because it teaches how to use Azure Databricks, a cloud-based data engineering platform. This course can help IT Consultants learn how to use Azure Databricks to develop and implement data solutions for their clients.
Data Governance Analyst
Data Governance Analysts work to ensure that data is managed in a consistent and compliant manner. They develop and implement data governance policies and procedures, and they work with stakeholders to ensure that data is used in an ethical and responsible manner. The Integrating Azure Databricks with Local Development Environments course may be useful for aspiring Data Governance Analysts because it teaches how to use Azure Databricks, a cloud-based data engineering platform. This course can help Data Governance Analysts learn how to use Azure Databricks to manage data in a consistent and compliant manner.

Reading list

We've selected six 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 Integrating Azure Databricks with Local Development Environments.
Practical guide to using Spark for big data analysis. It covers a wide range of topics, including data loading, transformation, and machine learning.
This authoritative guide offers in-depth knowledge of designing and building scalable, reliable, and maintainable data-intensive applications. It explores principles and patterns for data storage, processing, and analysis.
Is recommended for its in-depth coverage of Python libraries and tools for data analysis. It provides a solid foundation for working with data in Python, including data manipulation, visualization, and machine learning.
Focuses on applying Apache Spark for machine learning tasks. It covers topics such as data preparation, feature engineering, model training, and evaluation, providing a hands-on approach to building machine learning pipelines.
Comprehensive guide to Spark. It covers a wide range of topics, including the Spark architecture, programming model, and use cases.
This practical guide offers a beginner-friendly introduction to PyCharm. It covers key features, such as code navigation, refactoring, debugging, and testing, helping users enhance their Python development experience and productivity.

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