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Data Engineering on Microsoft Azure
176 students
Data Engineering on Microsoft Azure
DP 203 - Azure Data Engineer Associate
Created byKishore Chowdary
Last updated 4/2024
English
English [Auto],
What you'll learn
- Implement a partition strategy
- Design and implement the data exploration layer
- Ingest and transform data
- Develop a batch processing solution
- Develop a stream processing solution
- Manage batches and pipelines
- Implement data security
- Monitor data storage and data processing
- Optimize and troubleshoot data storage and data processing
Explore related topics
Course content
11 sections • 37 lectures • 6h 24m total length
Requirements
- Foundational Knowledge of Azure
Description
In this course, you will learn how to implement and manage data engineering workloads on Microsoft Azure, using Azure services such as Azure Synapse Analytics, Azure Data Lake Storage Gen2, Azure Stream Analytics, Azure Databricks, and others. The course focuses on common data engineering tasks such as orchestrating data transfer and transformation pipelines, working with data files in a data lake, creating and loading relational data warehouses, capturing and aggregating streams of real-time data, and tracking data assets and lineage.
You can become a data professional, a data architect, or a business intelligence professional by learning about data engineering and building analytical solutions using data platform technologies that exist on Microsoft Azure. This course will give you a flavor of end-to-end processing of big data in Azure.
As a candidate for this certification, you should have subject matter expertise in integrating, transforming, and consolidating data from various structured, unstructured, and streaming data systems into a suitable schema for building analytics solutions.
As an Azure data engineer, you help stakeholders understand the data through exploration, and build and maintain secure and compliant data processing pipelines by using different tools and techniques. You use various Azure data services and frameworks to store and produce cleansed and enhanced datasets for analysis.
Who this course is for:
- Data Engineers: Professionals who focus on preparing "big data" for analytical or operational uses. These individuals are responsible for designing, building, and maintaining the architecture (such as databases and large-scale processing systems) for data ingestion, processing, and analytics.
- Data Architects: These are professionals who design the blueprint for managing data across the organization. They work on designing data solutions that utilize Azure services effectively to meet both the technical and business requirements.
- Data Professionals: This broad category includes anyone working with data in a technical capacity and looking to leverage Azure's data services for their data solutions. This could include database administrators, data analysts, and software developers with a focus on data.
- IT Professionals: IT professionals who are not necessarily data specialists but are looking to expand their skills into the data engineering space can benefit from this course. This includes system administrators, software developers, and IT managers who need to understand how data solutions are designed and implemented on Azure.
- Students and Recent Graduates: Those who are studying in fields related to computer science, data science, information technology, or similar areas and are looking to enter the workforce with a strong set of skills in cloud-based data solutions.