Microsoft DP-203: Data Engineering on Microsoft Azure eLearning

COURSE DESCRIPTION

In this CertKit, 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.

• 12 Months Online Access
• 25+ hours of eLearning
• 20+ hours of Challenge Labs (90 days access)
• Online Mentor
• Measure-Up Exam simulation – 200 questions
• Tips & Tricks

CERTIFICATION

This course prepares participants for the official Microsoft DP-203 exam, which can be taken separately after completing the training. This exam is optional and can be ordered separately with the training course.

LEARNING OUTCOMES

• Explore compute and storage options for data engineering workloads in Azure
• Design and Implement the serving layer
• Understand data engineering considerations
• Run interactive queries using serverless SQL pools
• Explore, transform, and load data into the Data Warehouse using Apache Spark
•  Perform data Exploration and Transformation in Azure Databricks
• Ingest and load Data into the Data Warehouse.

TARGET AUDIENCE

The primary audience for this course is data professionals, data architects, and business intelligence professionals who want to learn about data engineering and building analytical solutions using data platform technologies that exist on Microsoft Azure. The secondary audience for this course data analysts and data scientists who work with analytical solutions built on Microsoft Azure.

CONTENT

• Storage Accounts
• Designing Data Storage Structures
• Data Partitioning
• Designing the Serving Layer
• Physical Data Storage Structures
• Logical Data Structures
• The Serving Layer
• Data Policies & Standards
• Securing Data Access
• Securing Data
• Data Lake Storage
• Data Flow Transformation
• Data Factory
• Databricks
• Databrick Processing
• Stream Analytics
• Synapse Analytics
• Data Storage Monitoring
• Data Process Monitoring
• Data Solution Optimization

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.