— DP-203T00

DP-203T00 | Data Engineering on Microsoft Azure

DP-203T00

DP-203

4 Day(s)

Instructor-Led Training

SGD $2600

Data Engineering on Microsoft Azure

Course Schedules

19 Dec 2022 - 22 Dec 2022
27 Feb 2023 - 02 Mar 2023
10 Apr 2023 - 13 Apr 2023
05 Jun 2023 - 08 Jun 2023
17 Oct 2022 - 20 Oct 2022

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Course OVERVIEW

In this course, the student will learn about the 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 compute 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 is 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 realtime analytical system to create real-time analytical solutions.

WHO IS THE COURSE FOR?

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.

ATTAINABLE SKILLS

• Explore compute and storage options for data engineering workloads in Azure
• Run interactive queries using serverless SQL pools
• Perform data Exploration and Transformation in Azure Databricks
• Explore, transform, and load data into the Data Warehouse using Apache Spark
• Ingest and load Data into the Data Warehouse
• Transform Data with Azure Data Factory or Azure Synapse Pipelines
• Integrate Data from Notebooks with Azure Data Factory or Azure Synapse Pipelines
• Support Hybrid Transactional Analytical Processing (HTAP) with Azure Synapse Link
• Perform end-to-end security with Azure Synapse Analytics
• Perform real-time Stream Processing with Stream Analytics
• Create a Stream Processing Solution with Event Hubs and Azure Databricks

LEARNING PATHWAY

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

Module 2: Run interactive queries using Azure Synapse Analytics serverless SQL pools

Module 3: Data exploration and transformation in Azure Databricks

Module 4: Explore, transform, and load data into the Data Warehouse using Apache Spark

Module 5: Ingest and load data into the data warehouse

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

Module 7: Orchestrate data movement and transformation in Azure Synapse Pipelines

Module 8: End-to-end security with Azure Synapse Analytics

Module 9: Support Hybrid Transactional Analytical Processing (HTAP) with Azure Synapse Link

Module 10: Real-time Stream Processing with Stream Analytics

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

FULL COURSE OUTLINE 👉

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