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Master Azure Data Engineering in an Intensive 3 Days.

Certified Azure Data Engineer Associate | Exam DP-203

2100,-€ (excl. VAT)

Cost

3 Days

Duration

By the end of this course, you'll understand how to implement, manage, and optimize data solutions on Azure. You'll be able to run interactive queries, secure data, manage users, transform data using various Azure tools, and much more. This course will empower you to meet your organization's data engineering needs effectively and become a valued Azure Data Engineer.

Learning Objectives

It's recommended that you have knowledge in data processing languages like SQL, Python, or Scala, and understand parallel processing and data architecture patterns. 


Even if you're unsure about your readiness, NEOEDX offers a consultation to ensure this course aligns with your skills and goals.

Prerequisites

This course is ideal for cloud DBAs, admins, solutions architects, and IT professionals responsible for data solutions in their organizations. Whether you're looking to validate your skills with a certification or seeking to implement advanced data solutions on Azure, this course provides the knowledge and hands-on experience you need.

Who Should Attend

Delve into the world of Azure Data Engineering with NEOEDX's accelerated course designed to elevate your skills in implementing, managing, and deploying data solutions on Microsoft Azure. In just 3 days, learn how to ensure high-performing, efficient, and reliable data pipelines and stores, meeting specific business requirements and constraints. Gain hands-on experience with Azure Synapse serverless SQL pools, Apache Spark Pools in Azure Synapse Analytics, and various data transformation and security techniques. This course is your gateway to becoming a proficient Azure Data Engineer, equipped to handle complex data challenges in today's cloud-driven landscape.

Course Description

  • Compute and Storage Options: For data engineering workloads.

  • Designing the Serving Layer: Implementing effective data presentation.

  • Data Engineering for Source Files: Best practices and considerations.

  • Interactive Queries with Azure Synapse: Using serverless SQL pools.

  • Data Transformation with Apache Spark: Loading data into the Data Warehouse.

  • Data Exploration in Azure Databricks: And transformation techniques.

  • Data Ingestion and Loading: Into the data warehouse.

  • Transforming Data: With Azure Data Factory and Synapse Pipelines.

  • Orchestration of Data Movement: In Azure Synapse Pipelines.

  • Optimising Query Performance: With dedicated SQL pools in Azure Synapse.

  • Data Warehouse Storage: Analysis and optimization.

  • Supporting HTAP: With Azure Synapse Link.

  • End-to-End Security: With Azure Synapse Analytics.

  • Real-Time Stream Processing: With Stream Analytics.

  • Stream Processing Solutions: With Event Hubs and Azure Databricks.

  • Reporting with Power BI: Integration with Azure Synapse Analytics.

  • Machine Learning in Azure Synapse: Performing integrated processes.

Course Outline

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