DP-203: Data Engineering on Microsoft Azure Certification Training

DP-203T00: Data Engineering on Microsoft Azure Certification Training Course Overview

Enroll for 3 day DP-203: Data Engineering on Microsoft Azure training course from Koenig Solutions accredited by Microsoft. In this course you will learn about  implementation and configuration, so you need to know how to create, manage, use, and configure data services in the Azure portal.

Through a blend of hands-on labs and interactive lectures, you will learn to build and maintain secure and compliant data processing pipelines by using different tools and techniques. These professionals use various Azure data services and languages to store and produce cleansed and enhanced datasets for analysis.

 

Target Audience:

  • Microsoft Azure Data Engineers
  • Microsoft Azure Data Scientist
  • Database and BI developers
  • Database Administrators
  • Data Analyst or similar profiles
  • On-Premises Database related profiles who want to learn how to implement these technologies in Azure Cloud.

Learning Objectives:

After completing this course, you will be able to:

  • Implementing Azure data storage solutions
  • Evolution of the Data Engineer role over the years
  • Managing and troubleshooting Azure data solutions
  • Monitoring and optimizing Azure data solutions
  • Working with Azure Databricks, Azure Data Factory, NoSQL, and more

 

 

This course prepares you for Exam DP-203. Test your current knowledge Qubits42

DP-203: Data Engineering on Microsoft Azure Certification Training (Duration : 32 Hours) Download Course Contents

Live Virtual Classroom
Group Training 1250
02 - 05 Aug 09:00 AM - 05:00 PM CST
(8 Hours/Day)

06 - 09 Sep 09:00 AM - 05:00 PM CST
(8 Hours/Day)

1-on-1 Training (GTR) 1450
4 Hours
8 Hours
Week Days
Week End

Start Time : At any time

12 AM
12 PM

GTR=Guaranteed to Run
Classroom Training (Available: London, Dubai, India, Sydney, Vancouver)
Duration : On Request
Fee : On Request
On Request
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Course Modules

Module 1: Explore compute and storage options for data engineering workloads
  • Introduction to Azure Synapse Analytics
  • Describe Azure Databricks
  • Introduction to Azure Data Lake storage
  • Describe Delta Lake architecture
  • Work with data streams by using Azure Stream Analytics
  • Explore compute and storage options for data engineering workloads
Module 2: Design and implement the serving layer
  • Design a multidimensional schema to optimize analytical workloads
  • Code-free transformation at scale with Azure Data Factory
  • Populate slowly changing dimensions in Azure Synapse Analytics pipelines
  • Designing and Implementing the Serving Layer
Module 3: Data engineering considerations for source files
  • Design a Modern Data Warehouse using Azure Synapse Analytics
  • Secure a data warehouse in Azure Synapse Analytics
Module 4: Run interactive queries using Azure Synapse Analytics serverless SQL pools
  • Explore Azure Synapse serverless SQL pools capabilities
  • Query data in the lake using Azure Synapse serverless SQL pools
  • Secure data and manage users in Azure Synapse serverless SQL pools
Module 5: Explore, transform, and load data into the Data Warehouse using Apache Spark
  • Understand big data engineering with Apache Spark in Azure Synapse Analytics
  • Ingest data with Apache Spark notebooks in Azure Synapse Analytics
  • Transform data with DataFrames in Apache Spark Pools in Azure Synapse Analytics
  • Integrate SQL and Apache Spark pools in Azure Synapse Analytics
Module 6: Data exploration and transformation in Azure Databricks
  • Describe Azure Databricks
  • Read and write data in Azure Databricks
  • Work with DataFrames in Azure Databricks
  • Work with DataFrames advanced methods in Azure Databricks
Module 7: Ingest and load data into the data warehouse
  • Use data loading best practices in Azure Synapse Analytics
  • Petabyte-scale ingestion with Azure Data Factory
Module 8: Transform data with Azure Data Factory or Azure Synapse Pipelines
  • Data integration with Azure Data Factory or Azure Synapse Pipelines
  • Code-free transformation at scale with Azure Data Factory or Azure Synapse Pipelines
Module 9: Orchestrate data movement and transformation in Azure Synapse Pipelines
  • Orchestrate data movement and transformation in Azure Data Factory
Module 10: Optimize query performance with dedicated SQL pools in Azure Synapse
  • Optimize data warehouse query performance in Azure Synapse Analytics
  • Understand data warehouse developer features of Azure Synapse Analytics
Module 11: Analyze and Optimize Data Warehouse Storage
  • Analyze and optimize data warehouse storage in Azure Synapse Analytics
Module 12: Support Hybrid Transactional Analytical Processing (HTAP) with Azure Synapse Link
  • Design hybrid transactional and analytical processing using Azure Synapse Analytics
  • Configure Azure Synapse Link with Azure Cosmos DB
  • Query Azure Cosmos DB with Apache Spark pools
  • Query Azure Cosmos DB with serverless SQL pools
Module 13: End-to-end security with Azure Synapse Analytics
  • Secure a data warehouse in Azure Synapse Analytics
  • Configure and manage secrets in Azure Key Vault
  • Implement compliance controls for sensitive data
Module 14: Real-time Stream Processing with Stream Analytics
  • Enable reliable messaging for Big Data applications using Azure Event Hubs
  • Work with data streams by using Azure Stream Analytics
  • Ingest data streams with Azure Stream Analytics
Module 15: Create a Stream Processing Solution with Event Hubs and Azure Databricks
  • Process streaming data with Azure Databricks structured streaming
Module 16: Build reports using Power BI integration with Azure Synapase Analytics
  • Create reports with Power BI using its integration with Azure Synapse Analytics
Module 17: Perform Integrated Machine Learning Processes in Azure Synapse Analytics
  • Use the integrated machine learning process in Azure Synapse Analytics
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Course Prerequisites

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