DP-203 Data Engineering on Microsoft Azure | Certification | Synergetics

Description

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 real-time analytical system to create real-time analytical solutions.

Course Duration: 4 Day(s)

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

Create a Stream Processing Solution with Event Hubs and Azure Databricks

Highlights

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

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Who Should Attend

Successful students start this course with knowledge of cloud computing and core data concepts and professional experience with data solutions. 

Specifically completing:

AZ-900 - Azure Fundamentals

DP-900 - Microsoft Azure Data Fundamentals

Target Audience

Data Engineer & Data Analyst

Personas

Data Engineer & Data Analyst