Data Engineering on Microsoft Azure (DP-203)

Category	ID	Duration	Level	Price
Azure	13782	4 Day(s)	Intermediate	$2,495.00

Class Schedule

Live Online

Location	Date	Time	Register
Live - Online	04/29/2024 - 05/02/2024	10:00 AM - 4:45 PM EST	Register
Live - Online	06/10/2024 - 06/13/2024	10:00 AM - 4:45 PM EST	Register
Live - Online	07/08/2024 - 07/11/2024	10:00 AM - 4:45 PM EST	Register
Live - Online	08/05/2024 - 08/08/2024	10:00 AM - 4:45 PM EST	Register
Live - Online	08/26/2024 - 08/29/2024	10:00 AM - 4:45 PM EST	Register
Live - Online	09/23/2024 - 09/26/2024	10:00 AM - 4:45 PM EST	Register
Live - Online	10/21/2024 - 10/24/2024	10:00 AM - 4:45 PM EST	Register

Course Overview

In this course, you 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. Begin by understanding the core compute and storage technologies that are used to build an analytical solution. You will then explore how to design an analytical serving layers and focus on data engineering considerations for working with source files. You will learn how to interactively explore data stored in files in a data lake. You will also 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.

Additionally, comprehend the various ways you can transform the data using the same technologies that are used to ingest data. You will spend time on the course learning how to monitor and analyze the performance of analytical system so that you can optimize the performance of data loads, or queries that are issued against the systems. You will understand the importance of implementing security to ensure that the data is protected at rest or in transit. You will then show how the data in an analytical system can be used to create dashboards, or build predictive models in Azure Synapse Analytics.

Course Objectives

After successfully completing this course, you will be able to:
● Explore compute and storage options for data engineering workloads in Azure
● Design and Implement the serving layer
● Understand data engineering considerations

Microsoft Certified: Azure Data Engineer Associate

Designing an Azure Data Solution Training (DP-201)

Administering Relational Databases on Microsoft Azure Training (DP-300)

Designing and Implementing a Data Science Solution on Azure (DP-100)

Designing and Implementing an Azure AI Solution (AI-100)

Analyzing Data with Power BI (DA-100)

Training Delivery Methods

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Data Engineering on Microsoft Azure (DP-203)

Class Schedule