Azure Data Engineer Associate (DP-203) Cert Prep: 2 Design and Develop Data Processing
46mIntermediate2022-01-06
Authors
Noah Gift
MLOps Expert | Solopreneur | Author | Adjunct Professor | CTO
Course details
Are you preparing for the Microsoft Azure Data Engineering (DP-203) exam, or seeking a better understanding of how to design and develop data processing? This course, the second in a series, can help you. Noah Gift, founder of Pragmatic A.I. Labs and a Python Software Foundation Fellow, covers how to design and develop data processing with Azure. Noah shows you how to use Apache Spark, Data Factory, and Databricks to ingest and transform data in Azure. He goes over data cleaning and common data transformation tasks, then dives into batch processing solutions. After explaining how to integrate Jupyter/Python notebooks into your data pipeline, Noah discusses stream processing, the differences between stream and batch processing, and using the Azure Data Factory solution to manage your batches and pipelines.
Skills covered
Data EngineeringAzureNetwork AdministrationCloud PlatformsCert PrepNetwork and System AdministrationCloud ComputingData ScienceMicrosoft
Concepts
0. Introduction
- 01 - Design and develop data processing on Microsoft Azure
- 02 - Quick prerequisite technology overview
1. Ingest and Transform Data
- 03 - Transform data by using Apache Spark
- 04 - Cleanse data
- 05 - Common data transform tasks
2. Design and Develop a Batch Processing Solution
- 06 - Develop batch processing solutions
- 07 - Integrate Jupyter Python notebooks
3. Design and Develop a Stream Processing Solution
- 08 - Develop a stream processing solution
4. Manage Batches and Pipelines
- 09 - Manage batches and pipelines
Conclusion
- 10 - Summary and next steps
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