Why Attend This Training Course?

In this course, participants will learn about data engineering as it pertains to working with batch and real-time analytical solutions using Azure data platform technologies. They 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 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. Participants 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 real-time analytical system to create real-time analytical solutions.

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What Is The Training Course Methodology?

This training course methodology depends on enabling participants to interact and exchange experiences, explore their competencies and achieve their career aspirations, using forward-thinking training arts, such as theoretical lectures and/or open discussion to exchange opinions and experiences, scenarios, innovative thinking brainstorming. Participants will receive an agenda including training material as a reference, in addition to some extra notes and booklets. 

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Who Should Attend This Training Course?

This training course is designed for participants with knowledge of cloud computing and core data concepts and professional experience with data solutions.

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What Are The Training Course Objectives?

• 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

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What Is The Training Course Curriculum?

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 Databrick