In this course, the student will learn how to implement and manage data engineering workloads on Microsoft Azure, using Azure services such as Azure Synapse Analytics, Azure Data Lake Storage Gen2, Azure Stream Analytics, Azure Databricks, and others. The focuses on common data engineering tasks such as orchestrating data transfer and transformation pipelines, working with data files in a data lake, creating and loading relational data warehouses, capturing and aggregating streams of real-time data, and tracking data assets and lineage.
The DP-203 Data Engineering on Microsoft Azure certification training is crafted to equip individuals with the expertise and skills required to excel in data engineering within the Microsoft Azure cloud environment. This course delves into data engineering concepts, Azure data services, and the practical implementation of data pipelines and transformations. Successful completion of this training will prepare individuals for the DP-203 certification exam and enable them to pursue roles as data engineers, responsible for designing, building, and maintaining data solutions in Microsoft Azure to support data-driven decision-making within organizations.
Successful students start this course with knowledge of cloud computing and core data concepts and professional experience with data solutions.
Specifically completing:
AZ-900 - Azure Fundamentals
DP-900 - Microsoft Azure Data Fundamentals
1)Introduction to data engineering on Azure
2) Introduction to Azure Data Lake Storage Gen2
3)Introduction to Azure Synapse Analytics
4)Use Azure Synapse serverless SQL pool to query files in a data lake
5)Use Azure Synapse serverless SQL pools to transform data in a data lake
6)Create a lake database in Azure Synapse Analytics
7)Analyze data with Apache Spark in Azure Synapse Analytics
8)Transform data with Spark in Azure Synapse Analytics /Use Delta Lake in Azure Synapse Analytics
9) Analyze data in a relational data warehouse
10) Load data into a relational data warehouse
11) Build a data pipeline in Azure Synapse Analytics
12)Use Spark Notebooks in an Azure Synapse Pipeline
13)Plan hybrid transactional and analytical processing using Azure Synapse Analytics
14) Implement Azure Synapse Link with Azure Cosmos DB
15) Implement Azure Synapse Link for SQL
16)Get started with Azure Stream Analytics
17) Ingest streaming data using Azure Stream Analytics and Azure Synapse Analytics
18) Visualize real-time data with Azure Stream Analytics and Power BI
19) Introduction to Microsoft Purview
20) Integrate Microsoft Purview and Azure Synapse Analytics
21) Explore Azure Databricks
22) Use Apache Spark in Azure Databricks
23) Run Azure Databricks Notebooks with Azure Data Factory