Data Engineering on Microsoft Azure
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Course Overview
Master Azure Data Engineering with Upskilled Tech Academy's DP-203 course. Gain expertise in integrating diverse data sources, architecting secure pipelines, and leveraging Azure services for efficient data processing. Explore, learn, and excel in crafting robust data solutions within the Azure ecosystem.
At Upskilled Tech Academy, our DP-203 course is meticulously designed for individuals aspiring to excel in Azure Data Engineering. Unveil the intricacies of integrating, transforming, and managing diverse data sources within the Azure ecosystem, aimed at crafting efficient and secure data solutions.
Why should you do this course?
- Master the art of integrating and managing diverse data sources in Azure.
- Explore essential tools and techniques for secure data processing.
- Engage in real-world case studies for practical insights.
- Prepare comprehensively for the DP-203 certification exam.
Who is this course for?
- Data professionals seeking mastery in Azure data services.
- IT specialists transitioning to Azure Data Engineering roles.
- Individuals pursuing the Azure Data Engineer Associate certification.
What you need to know
Dive into Azure Data Engineering with DP-203T00 at Upskilled Tech Academy—a comprehensive course unraveling data integration, processing, and management within Azure's ecosystem.
What's Next?
Upon completion, you'll be equipped to tackle the official Exam DP-203: Data Engineering on Microsoft Azure.
Skills Measured
- Design and implement data storage
- Develop data processing
- Secure, monitor, and optimise data storage and data processing
Course Structure
This course will provide in-depth coverage of the following topics:
Introduction to data engineering on Azure
Introduction to Azure Data Lake Storage Gen2
Introduction to Azure Synapse Analytics
Use Azure Synapse serverless SQL pool to query files in a data lake
Use Azure Synapse serverless SQL pools to transform data in a data lake
Create a lake database in Azure Synapse Analytics
Analyze data with Apache Spark in Azure Synapse Analytics
Transform data with Spark in Azure Synapse Analytics
Use Delta Lake in Azure Synapse Analytics
Analyze data in a relational data warehouse
Load data into a relational data warehouse
Build a data pipeline in Azure Synapse Analytics
Use Spark Notebooks in an Azure Synapse Pipeline
Plan hybrid transactional and analytical processing using Azure Synapse Analytics
Implement Azure Synapse Link with Azure Cosmos DB
Implement Azure Synapse Link for SQL
Get started with Azure Stream Analytics
Ingest streaming data using Azure Stream Analytics and Azure Synapse Analytics
Visualize real-time data with Azure Stream Analytics and Power BI
Introduction to Microsoft Purview
Integrate Microsoft Purview and Azure Synapse Analytics
Explore Azure Databricks
Use Apache Spark in Azure Databricks
Run Azure Databricks Notebooks with Azure Data Factory
Entry requirements
As a candidate for this course, you must have solid knowledge of data processing languages, including:
- SQL
- Python
- Scala
You need to understand parallel processing and data architecture patterns. You should be proficient in using the following to create data processing solutions:
- Azure Data Factory
- Azure Synapse Analytics
- Azure Stream Analytics
- Azure Event Hubs
- Azure Data Lake Storage
- Azure Databricks
Pricing Options
FAQs
The DP-203 course is ideal for data professionals, database administrators, and IT specialists aiming to specialize in Azure Data Engineering. It's also suitable for individuals pursuing the Azure Data Engineer Associate certification.
The course covers essential areas such as data integration, transformation, and management within Azure. It includes working with Azure data services like Data Factory, Synapse Analytics, Databricks, Stream Analytics, and more.
Participants will acquire skills in integrating diverse data sources, designing secure and efficient data pipelines, optimizing data solutions, and ensuring compliance within Azure.
Candidates should have a solid understanding of data management concepts, familiarity with Azure fundamentals, and proficiency in data processing languages like SQL, Python, or Scala.
