DP-203: Data Engineering on Microsoft Azure

DP-203: Data Engineering on Microsoft Azure

In this course, the student will learn about the data engineering patterns and practices as it pertains to working with batch and real-time analytical solutions using Azure data platform technologies. Students will begin by understanding the core compute and storage technologies that are used to build an analytical solution. They will then explore how to design an analytical serving layers and focus on data engineering considerations for working with source files.

The students will learn how to interactively explore data stored in files in a data lake. They will learn the various ingestion techniques that can be used to load data using the Apache Spark capability found in Azure Synapse Analytics or Azure Databricks, or how to ingest using Azure Data Factory or Azure Synapse pipelines. The students will also learn the various ways they can transform the data using the same technologies that is used to ingest data.

The student will spend time on the course learning how to monitor and analyze the performance of analytical system so that they can optimize the performance of data loads, or queries that are issued against the systems. They will understand the importance of implementing security to ensure that the data is protected at rest or in transit.

This course will build on these topics with hands-on lab learnings and Knowledge Check questions.

Microsoft Courseware

Instructor-Led Training

Course Duration: 4-Days (32-Hour)

Microsoft Official Lab Exercises

Courseware Life Time Free Upgrade

Cloud Lab Access

Overview


The audience for this course are data engineers, data professionals, data architects, and business intelligence professionals who want to learn about the data platform technologies that exist on Microsoft Azure that can be used to perform data engineering and storage for analytical solutions. The secondary audience for this course are individuals who develop applications that deliver content from the data platform technologies that exist on Microsoft Azure.


The students will learn how to interactively explore data stored in files in a data lake. They will learn the various ingestion techniques that can be used to load data using the Apache Spark capability found in Azure Synapse Analytics or Azure Databricks, or how to ingest using Azure Data Factory or Azure Synapse pipelines. The students will also learn the various ways they can transform the data using the same technologies that is used to ingest data.


Prerequisites
In addition to their professional experience, students who take this training should have technical knowledge equivalent to the Azure Data fundamentals course.

Modules

Module 1: Explore compute and storage options for data engineering workloads

  • Introduction to Azure Synapse Analytics
  • Introduction to Azure Databricks
  • Describe Azure Databricks Delta Lake Architecture
  • Introduction to Azure Data Lake storage
  • Work with data streams by using Azure Stream Analytics

Module 2: Run Interactive queries using serverless SQL pools

  • Explore Azure Synapse serverless SQL pools capabilities
  • Query data in the lake using Azure Synapse serverless SQL pools
  • Create metadata objects in Azure Synapse serverless SQL pools
  • Secure data and manage users in Azure Synapse serverless SQL pools

Module 3: 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 4: 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
  • Monitor manage data engineering workloads with Apache Spark Azure Synapse Analytics

Module 5: Ingest and load Data into the Data Warehouse

  • Use data loading best practices in Azure Synapse Analytics
  • Petabytes-scale ingestion with Azure Data Factory

Module 6: Transform Data with Azure Data Factory or Azure Synapse Pipelines

  • Data integration with Azure Data Factory
  • Perform code-free transformation at scale with Azure Data Factory

Module 7: Integrate Data from Notebooks with Azure Data Factory or Azure Synapse Pipelines

  • Orchestrating data movement and transformation in Azure Data Factory

Module 8: 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 9: Support Hybrid Transactional Analytics 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 for Azure Synapse Analytics
  • Query Azure Cosmos DB with SQL Serverless for Azure Synapse Analytics

Module 10: 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
  • Transform data by using Azure Stream Analytics

Module 11: Create a Stream Processing Solution with Event Hubs and Azure Databricks

  • Process streaming data with Azure Databricks structured streaming

Fees And Schedule

Instructor-Led Training

32-Hour of Instructor-Led Training One to one doubt resolution sessions Microsoft Official Lab Access

Learning Objectives

After completing the course, students will be able to:

  • Design and implement data storage
  • Design and develop data processing
  • Design and implement data security
  • Monitor and optimize data storage and data processing

Reviews

Dipak Agarwal - Business Analyst at Genpact

(5/5)
Excellent professional & comfortable environment to learn

The training was good, I would like to go through some more training.

Gurpreet Marwaha - IAM Analyst at National Australia Bank, Australia

(5/5)
I learned a lot

Excellent Office 365 training provided by Flexmind

Kiranmai Yachareni - Web Developer at Total Quality Logistics, USA

(5/5)
Excellent ability to clarify all the queries I raised

Thank You! I would definitely recommend it to others. The training session was very informative and interactive. Very useful and definitely thought-provoking. All the module sessions were clear and interactive, great, and friendly. Catered to all levels, which was good for those just starting out and those with more experience. I really appreciate the recorded videos and training material, which would be definitely helpful for later references.

Praveen S (Associate at Grant Thornton LLP)

(5/5)
Excellent knowledge of the trainer on the Subject

I attended PowerApps/Flow training from Flexmind. The topics of the course were well organized & knowledge of the trainer on the subject was excellent. It was very helpful and I will apply in my day to day task at the office. I will definitely recommend a friend or colleague to attend courses from Flexmind.

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