- Duration: 5 Days
Course Overview:
They will learn about the data engineering patterns and practices 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. They will then explore how to design an analytical serving layer and focus on data engineering considerations for working with source files. 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.
Learning Objectives
- Explore compute and storage options for data engineering workloads in Azure.
- Design and implement the serving layer.
- Understand data engineering considerations
- Run interactive queries using serverless SQL pools
- Explore, transform, and load data into the Data Warehouse using Apache Spark.
Target Audience
This course is designed for individuals who have basic computer user skills and who are interested in obtaining a job as an entry-level IT technician.
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