Free Download DP-203 Azure Data Engineer Associate Exam Preparation
Last updated 3/2024
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Language: English | Duration: 11h 52m | Size: 7.7 GB
Pass DP203: Synapse|DataLake|DataFactory|Databricks|StreamAnalytics with performance and security improvements explained
What you'll learn
Prepare comprehensively for the Azure Data Engineer Associate (DP-203) exam with an emphasis on practical skills and knowledge application.
Understand the exam format for DP 203 and key areas of focus to successfully achieve certification.
Master Data Processing with Azure Synapse for DP203
Ensure robust Security, and optimize Performance within Azure Synapse
Comprehend Azure Data Lake Storage Solutions
Orchestrate Data Workflows with Azure Data Factory
Introduction to Azure Databricks for Collaborative Data Engineering
Learn Real-Time Data Processing with Azure Stream Analytics
Become proficient in leveraging Azure's data engineering tools to their fullest potential, ready to thrive as a data engineer in the Azure cloud ecosystem.
Requirements
Prerequisites: Basic SQL
Description
Dive into the world of Azure Data Engineering with a focused and comprehensive course designed to prepare you for the Azure Data Engineer Associate exam: DP-203
This course provides a comprehensive exploration of Azure Synapse Analytics and its integrated ecosystem, encompassing Dedicated SQL Pools, Serverless SQL Pools, and Spark Pools.
You will understand how to harness the power of massive parallel processing in Dedicated SQL Pool by mastering Distributions and Indexing. The course also emphasizes performance optimization in Synapse's Dedicated SQL Pools, highlighting techniques like Partitioning, the use of Dynamic Management Views, Materialized Views, and effective Workload Management strategies. Additionally, you'll acquire skills in enhancing security for Dedicated SQL Pools through measures such as Conditional Access, Dynamic Data Masking, Column-level Security, Row-level Security and Encryption.
You will Learn how to utilize Serverless SQL Pools for efficient on-demand data queries and transformations and also about the authentication strategies for Serverless SQL Pools.
The curriculum thoroughly covers Spark Pools, introducing concepts like Delta Lake and Data Lakehouse.
We'll cover the Data Lake for scalable storage solutions, focusing on key features like Access Control Lists (ACLs) for securing data, Lifecycle Policies for managing data retention, different Access Tiers available in Azure Data Lake Storage to store data cost-effectively based on access frequency and retrieval needs, and Storage Redundancy for data durability. This will give you a solid foundation in managing vast amounts of data securely and efficiently in Azure.
You'll dive into the basics of Azure Data Factory, laying a foundation for understanding how to orchestrate data movement and transformation workflows effectively and you'll learn the fundamentals of creating, managing, and deploying data pipelines that enable efficient data flow between different data platforms and services within the Azure ecosystem.
Azure Databricks sessions will introduce you to collaborative Apache Spark-based Data Engineering along with explanations on different cluster configurations.
Finally, the course delves into Azure Stream Analytics for real-time data processing. You will learn to ingest, process, and analyse data streams in real-time with a better understanding of time handling strategies within Stream Analytics like Out of order events, Late arriving events, Early arriving events and Watermarks.
This course not only prepares you for the Azure Data Engineer Associate exam but also equips you with the practical skills and knowledge needed to thrive as a data engineer in the Azure cloud ecosystem. Through a blend of theoretical knowledge and practical demonstrations, you'll emerge ready to tackle real-world data challenges and leverage Azure's powerful data engineering tools to their fullest potential.
Who this course is for
Data Engineers
Cloud Engineers
Data Analysts
IT Professionals
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