The recommended order of courses to prepare for the DP-203 Data Engineering on Microsoft Azure Certification are as follows: * Building an Azure Data Engineer Foundation * Data Ingestion and Preparation * Processing in Azure Using Batch Solutions * Processing in Azure Using Streaming Solutions * Secure, Monitor, and Optimize Data Storage and Processing Finally, use the Practice Exams to test your understanding for the Exam. In this course, Processing in Azure using Streaming Solutions, you will learn about processing data streams using Azure Event Hubs, Stream Analytics, and Databricks. The material covered in this course is what you need to know when preparing for the *Develop a Stream Processing Solution* section of the DP-203 exam. Processing data in a stream, instead of per batch, is particularly useful in scenarios where you need near-real time answers to queries as soon as new data points come in. Examples are detecting and preventing fraudulent transactions and monitoring social media comments. In Azure, there are three services you'll use when working with streaming data: * Azure Event Hubs for ingesting and buffering data * Azure Stream Analytics for processing and transforming datastreams * Azure Databricks for processing and transforming data streams In this course, you will learn how to work with these services to: * Ingest data from streaming data sources * How to write Stream Analytics queries that produce results based on query windows * Partition data streams for scale * Deal with adversity * And more If you are preparing to take the DP-203 exam, this course will help you get ready for the section on streaming data.
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Activities
Read 'Designing Data-Intensive Applications'
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Expand your knowledge of data engineering principles and best practices by reading this foundational book.
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Secret Colors
on Amazon
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Identify a Senior Data Engineer as a Mentor
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Seek guidance from an experienced senior data engineer to accelerate your learning and development.
Show steps
-
Identify a senior data engineer with expertise in the areas you want to improve
-
Reach out and request a mentorship opportunity
-
Schedule regular meetings to discuss your goals and progress
Explore Azure Databricks Notebooks
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Familiarize yourself with the Azure Databricks notebook interface and learn how to create and run notebooks.
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-
Create a new notebook in Azure Databricks
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Import data into the notebook
-
Write a simple data transformation or analysis script
-
Run the script and visualize the results
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Practice Azure Data Lake Gen2 Querying
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Practice queries on data stored in Azure Data Lake Gen2 to familiarize yourself with the syntax and command structure.
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-
Create a sample data set in Azure Data Lake Gen2
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Install the Azure Data Lake Storage Gen2 NuGet package
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Write a query using the Azure Data Lake Storage Gen2 API
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Execute the query and examine the results
Attend an Azure Data Engineering Meetup
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Network with other data engineers and learn about the latest trends and technologies in the field.
Show steps
-
Find an Azure Data Engineering Meetup in your area
-
Attend the meetup
-
Introduce yourself to other attendees
Compile Azure Data Engineering Resources
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Organize and maintain a collection of useful resources, such as tutorials, articles, and code samples, related to Azure data engineering.
Show steps
-
Create a central repository for the resources
-
Regularly search for and add new relevant resources
-
Categorize the resources for easy retrieval
-
Share the repository with other data engineers
Build a Data Ingestion Pipeline
Show steps
Create a data ingestion pipeline that demonstrates your understanding of the data flow and transformation process.
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-
Design the data ingestion architecture
-
Implement the data ingestion pipeline using Azure services
-
Test and validate the pipeline
-
Document the pipeline
Mentoring Junior Data Engineers
Show steps
Share your knowledge and experience by mentoring junior data engineers and guiding them through their learning journey.
Show steps
-
Identify a junior data engineer who could benefit from your mentorship
-
Schedule regular meetings to provide guidance and support
-
Share resources and materials to support their learning
-
Provide feedback and encouragement to help them develop their skills
Read 'Designing Data-Intensive Applications'
Show steps
Expand your knowledge of data engineering principles and best practices by reading this foundational book.
View
Secret Colors
on Amazon
Show steps
Identify a Senior Data Engineer as a Mentor
Show steps
Seek guidance from an experienced senior data engineer to accelerate your learning and development.
Show steps
- Identify a senior data engineer with expertise in the areas you want to improve
- Reach out and request a mentorship opportunity
- Schedule regular meetings to discuss your goals and progress
Explore Azure Databricks Notebooks
Show steps
Familiarize yourself with the Azure Databricks notebook interface and learn how to create and run notebooks.
Show steps
- Create a new notebook in Azure Databricks
- Import data into the notebook
- Write a simple data transformation or analysis script
- Run the script and visualize the results
Practice Azure Data Lake Gen2 Querying
Show steps
Practice queries on data stored in Azure Data Lake Gen2 to familiarize yourself with the syntax and command structure.
Show steps
- Create a sample data set in Azure Data Lake Gen2
- Install the Azure Data Lake Storage Gen2 NuGet package
- Write a query using the Azure Data Lake Storage Gen2 API
- Execute the query and examine the results
Attend an Azure Data Engineering Meetup
Show steps
Network with other data engineers and learn about the latest trends and technologies in the field.
Show steps
- Find an Azure Data Engineering Meetup in your area
- Attend the meetup
- Introduce yourself to other attendees
Compile Azure Data Engineering Resources
Show steps
Organize and maintain a collection of useful resources, such as tutorials, articles, and code samples, related to Azure data engineering.
Show steps
- Create a central repository for the resources
- Regularly search for and add new relevant resources
- Categorize the resources for easy retrieval
- Share the repository with other data engineers
Build a Data Ingestion Pipeline
Show steps
Create a data ingestion pipeline that demonstrates your understanding of the data flow and transformation process.
Show steps
- Design the data ingestion architecture
- Implement the data ingestion pipeline using Azure services
- Test and validate the pipeline
- Document the pipeline
Mentoring Junior Data Engineers
Show steps
Share your knowledge and experience by mentoring junior data engineers and guiding them through their learning journey.
Show steps
- Identify a junior data engineer who could benefit from your mentorship
- Schedule regular meetings to provide guidance and support
- Share resources and materials to support their learning
- Provide feedback and encouragement to help them develop their skills
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