Microsoft DP-203 Certified: Azure Data Engineer Associate
What you'll learn
- This course is ideal for students aspiring to achieve the "Microsoft Certified: Azure Data Engineer Associate" Dp-203 certification.
- It includes comprehensive content aligned to pass DP-203 exam.
- Students will gain hands-on experience in implementing and managing data engineering workloads using Microsoft Azure.
- The course covers key Azure services, including Azure Synapse Analytics, ADF, Azure Data Lake Storage Gen2, Azure Stream Analytics, and Azure Databricks.
- Past Papers and Practice: Access to 500 exam questions to solidify knowledge and prepare for certification.
Requirements
- Prerequisites:
- Familiarity with any database system and basic proficiency in SQL is good to have.
- A foundational knowledge of data formats is expected. e.g csv etc
Description
This course is ideal for students aspiring to achieve the "Microsoft Certified: Azure Data Engineer Associate" certification.
It includes comprehensive content aligned with the DP-203 exam.
The course objectives focus on the following areas:
Design and implement data storage (15–20%)
Develop data processing (40–45%)
Secure, monitor, and optimize data storage and data processing (30–35%)
This Course structure organizes the course into a logical progression while providing a clear breakdown of the covered topics. Here’s is the structured outline of the course sections:
1. Introduction and Setup
Overview of the course and initial setup.
2. Design and Implement Data Storage
Azure Data Lake: Understanding and implementing data storage with Azure Data Lake.
Azure SQL Server: Designing storage solutions using Azure SQL Server.
Cosmos DB: Exploring storage capabilities with Cosmos DB.
Azure Synapse Analytics: Building and managing storage in Azure Synapse Analytics.
3. Develop Data Processing
Azure Synapse Spark Pool: Leveraging Spark pools in Azure Synapse for data processing.
Azure Data Factory: Developing ETL pipelines and data flows in Azure Data Factory.
Azure Databricks: Implementing data processing workflows with Azure Databricks.
Azure Event Hubs: Streaming and processing real-time data using Azure Event Hubs.
Azure Stream Analytics: Real-time data stream processing with SQL-based queries.
4. Secure Your Data
Azure Data Lake Security: Implementing security best practices for Azure Data Lake.
Azure Synapse Analytics Security: Securing data in Azure Synapse Analytics.
Azure Data Factory and Databricks Security: Ensuring secure data workflows in Azure Data Factory and Databricks.
4. Monitor and Optimize
Azure Data Lake Storage: Monitoring and optimizing storage performance.
Azure Data Factory: Ensuring efficient operations with monitoring tools.
Azure Synapse Analytics: Performance tuning and monitoring analytics workloads.
Azure Stream Analytics and Cosmos DB: Streamlining data streams and database operations.
Data Governance with Microsoft Purview: Managing and governing data using Microsoft Purview.
5. Exam Preparation
Past Papers and Practice: Access to 500 exam questions to solidify knowledge and prepare for certification.
Who this course is for:
- If you want to boost your career in the field of data engineering.
- Professional who will like to transform yourself into a skilled data engineer, this course is for you.
- Mastering DP-203 empowers you to build analytical solutions using Microsoft Azure's data platform technologies, paving the way for a successful career in data engineering.
- This course is tailored for data professionals, and BI and Data Analytics specialists aiming to deepen their knowledge of data engineering.
Instructor
- 4.2 Instructor Rating
- 98 Reviews
- 16,979 Students
- 2 Courses
Build on a diverse and prestigious educational background, I have combined practical industry experience of over 10 years of experience with an impressive array of certifications. This unique blend of expertise offers students an unparalleled learning experience, bridging the gap between data science and engineering.
Instructor Highlights:
· Microsoft Certified Data Engineer & IBM Certified Data Scientist: Expertise in data engineering and science, providing students with the skills to harness data technologies and methodologies effectively.
· Masters in Supply Chain Management & Artificial Intelligence: Holding prestigious credentials in both Supply Chain Management and Artificial Intelligence, I provide deep insights into optimizing supply chains for efficiency, sustainability, and resilience, as well as leveraging AI for innovative solutions across various domains. These qualifications allow me to offer a comprehensive perspective on how advanced analytics and AI technologies can transform industries.
· Industrial Engineering & Six Sigma: A strong foundation in industrial engineering, enhanced by Six Sigma methodologies, equips me with the tools to drive process improvement and operational excellence through data driven decision making.
Instructor Philosophy:
Focused on delivering a comprehensive educational experience, I integrate theoretical knowledge with practical applications. Courses are designed to cater to both beginners and seasoned professionals, emphasizing the development of critical thinking and problem-solving skills in the context of data engineering and analytics.
As an instructor my approach goes beyond traditional teaching methods more focused on hand on practice, offering a holistic view of how data science and engineering principles can be applied to real-world challenges. Students are not only prepared for current industry demands but are also equipped to lead future innovations.