DP-203: Microsoft Azure Data Engineer

In this four-day training, you will learn about data engineering an use batch- and real-time analytical solutions using Azure data platform technologies.

The training will introduce you to Azure core compute and storage technologies, how to ingest data into Azure Synapse Analytics or Azure Databricks, and how to design data loading pipelines with Azure Data Factory or Azure Synapse pipelines. You’ll also learn various ways to transform and analyze data, how to secure your data infrastructure, and how to create real-time analytical solutions in the Azure cloud.

This training prepares you for the Azure Data Engineer exam and certification.

Here’s What You’ll Get

Training Manual

Hands-On Lab

Cloud Credit

Private Slack Channel

Unlimited Teams Calls

Exam Voucher

Certificate of Completion

Self-Paced or Classroom Training

180-day Lab Access

Training Details

In this four-day training, you will learn about data engineering and work with batch- and real-time analytical solutions using Azure data platform technologies.

The training will introduce you to Azure compute and storage services that you’ll use to build an analytical solution. You’ll learn how to ingest data into Azure Synapse Analytics or Azure Databricks using Azure Data Factory or Azure Synapse pipelines. You’ll also learn how to extract, transform and load data into a data warehouse and how to secure your data infrastructure in the cloud.

As part of this training, you’ll receive an Azure Pass with credits to spend on your own cloud services. The pass is valid for 30 days.

Name: DP-203: Microsoft Azure Data Engineer

Format: Classroom

Content: training manual, online lab, Azure cloud credit, practice exam, and an exam voucher

Requirements: a laptop with a web browser installed. Chrome or Edge is recommended.

Support: Live classroom support

Associated certification: Microsoft Azure Data Engineer

Training Curriculum

Explore Azure data services

Azure Synapse Analytics

Azure Databricks

Azure Data Lake

The Delta Lake architecture

Azure Stream Analytics

Lab exercises

Build a streaming & batch pipeline

Create a Delta Lake

Index data lake storage

Synapse Analytics serverless pools

Synapse Analytics pool capabilities

The serverless SQL pool

Querying data

Creating and using external tables

Securing data

Lab exercises

Query Parquet data

Create external tables to read data

Create views

Secure access to data

Configure role-based access control

Azure Databricks

Read and write data

Working with DataFrames

Advanced dataframe functions

Lab exercises

Explore data with DataFrames

Cache data for faster queries

Remove duplicate data

Working with date/time values

Remove and rename columns

Aggregate data

Apache Spark notebooks

Apache Spark in Azure Synapse Analytics

Ingest data into Spark notebooks

Transform data with DataFrames

Integrate Spark and SQL pools

Lab exercises

Explore data in Synapse Studio

Ingest data into a Spark notebook

Transform data with DataFrames

Integrate Spark and SQL pools

Ingest & load data warehouse data

Data loading best practices

Petabyte-scale data ingestion with Azure Data Factory

Lab exercises

Ingest data with Azure Synapse pipelines

Import data with Polybase and COPY

Use data loading best practices

Azure pipelines

Data Factory and Synapse pipelines

Code-free data transformation at scale

Lab exercises

Transform data with Azure pipelines

Build a pipeline to load a malformed CSV file

Create a mapping data flow

Data orchestration in Azure pipelines

Orchestrate data movement & transformation

Set up linked services

Execute notebooks from a pipeline

Lab exercises

Integrate data from notebooks in an Azure Data Factory or Synapse pipeline

End-to-end security

Secure a data warehouse

Configure & manage secrets in Key Vault

Implement compliance controls

Lab exercises

Secure Synapse Analytics infrastructure

Secure workspace & managed services

Secure workspace data

Hybrid Transactional Analytical Processing (HTAP)

Designing HTAP solutions

Configure HTAP in Cosmos DB

Query Cosmos with a Spark pool

Query Cosmos with a SQL pool

Lab exercises

Configure HTAP in Cosmos DB

Query Cosmos with Apache Spark

Query Cosmos with serverless SQL pools

Azure Stream Analytics

Azure Event Hub

Azure Stream Analytics

Ingest data with Stream Analytics

Lab exercises

Process real-time data

Using windowing functions

Scaling Stream Analytics jobs

Repartitioning input streams

Real-time data in Azure Databricks

Process real-time data with Databricks

Lab exercises

Explore structured streaming

Stream a file to HDFS

Using sliding windows

Applying watermarking

Connecting to Event Hubs

Book a Classroom Training

Classroom trainings are conducted during business hours and hosted online or on-site at your place of work. All students need to participate is a laptop, a web browser, and Microsoft Teams.

Please use the form below to book a call with me to set up your classroom training. We’ll discuss your business requirements, team size, and preferred location of the training (online or on-site) and make sure you get what you need. A typical classroom training can usually be scheduled within 30 days and can accomodate up to 15 people on-site and 30 people online.

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