Overview
In this course, the student will learn about data engineering as it pertains to working with batch and real-time analytical solutions using Azure data platform technologies. Students will begin by understanding the core computing and storage technologies that are used to build an analytical solution. 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 are used to ingest data. They will understand the importance of implementing security to ensure that the data is protected at rest or in transit. The student will then show how to create a real-time analytical system to create real-time analytical solutions.
This course is designed for individuals who aim to understand the fundamentals of database concepts in a cloud environment, acquire basic skills in cloud data services, and deepen their foundational knowledge of Microsoft Azure’s data services.
Roles
- Database Engineer
What You'll Learn
- Design and implement various stages and concepts in the data engineering lifecycle (storage, processing, security) in Microsoft Azure
- Create and perform data service operations (monitoring and optimization) in Microsoft Azure
Skills You'll Gain
- Data Science
- Azure
Total hours
- Sync Hands-on/Lecture: 12 Hours
- Async Learning: 11 Hours
- Assessment: 9 hours
Course outline
Required resources
Laptop, Intel Core i5 or higher, 16GB RAM, 1TB Storage, Graphics Card (Hardware); Microsoft Azure (Software); Adequate Internet Connection (Network)
Pre-Requisites
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 are data analysts and data scientists who work with analytical solutions built on Microsoft Azure.
Assessment
Practical Assessment: Hands-on activities are prepared to assess the attainment of learning outcomes.
Final Assessment: This exam is an opportunity to demonstrate knowledge of core data concepts and related Microsoft Azure data services.Â
Credit and Recognition
The learner is eligible to take the Microsoft Certified: Azure Data Engineer Associate.
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This course is accredited by Microsoft and is facilitated by a Microsoft Certified professional.
