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DP-203T00 | Data Engineering on Microsoft Azure

DP-203T00

DP-203

4 Day(s)

Instructor-Led Training

from SGD $2600*

Course Schedules

05 Feb 2024 - 08 Feb 2024
15 Apr 2024 - 18 Apr 2024
18 Jul 2024 - 21 Jul 2024
05 Aug 2024 - 08 Aug 2024
04 Dec 2023 - 07 Dec 2023

TELL YOUR FRIENDS

Exam Code

DP-203

Course Duration

4 Day(s)

Delivery Mode

Instructor-Led Training

Course Price

from $2600
*Course Pricing Subjected to Terms & Conditions.

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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