Data Engineering on Microsoft Azure (DP203)

1. Focus on Azure Data Services: Emphasizes designing and implementing data storage solutions using various Azure data services.
2. Data Ingestion and Processing: Covers techniques for ingesting, processing, and transforming data from various sources.
3. Data Orchestration: Addresses orchestrating data workflows using Azure Data Factory and other Azure services.
4. Data Security and Compliance: Includes security features and compliance requirements for Azure data storage solutions.
5. Performance Optimization: Discusses methods for optimizing data storage and processing performance in Azure.
6. Integration with Azure Services: Explores integration with other Azure services for building end-to-end data solutions.

Before learning Data Engineering on Microsoft Azure (DP203), it's beneficial to have the following skills:

1. Fundamental Azure Knowledge: Understanding of basic Azure services and concepts, such as Azure Storage, Azure SQL Database, Azure Data Factory, Azure Databricks, and Azure Cosmos DB.

2. Data Fundamentals: Knowledge of data storage concepts, data formats (e.g., JSON, CSV), and data processing techniques.

3. SQL and Database Management: Proficiency in SQL querying and database management concepts.

4. Programming Skills: Familiarity with programming languages like Python, Scala, or SQL for data manipulation and scripting tasks.

5. Data Ingestion Techniques: Understanding of data ingestion methods and tools for extracting data from various sources.

6. Data Transformation and Processing: Knowledge of data transformation techniques and tools for processing and transforming raw data into usable formats.

By learning Data Engineering on Microsoft Azure (DP203), you gain the following skills:

1. Azure Data Services: Proficiency in utilizing various Azure data services such as Azure Storage, Azure SQL Database, Azure Data Factory, Azure Databricks, and Azure Cosmos DB.

2. Data Ingestion and Processing: Ability to ingest, process, and transform data from diverse sources using Azure Data Factory, Databricks, and other Azure tools.

3. Data Orchestration: Skills in orchestrating complex data workflows and pipelines using Azure Data Factory and other orchestration tools.

4. Data Security and Compliance: Knowledge of implementing security features and ensuring compliance with data governance regulations in Azure data solutions.

5. Performance Optimization: Capability to optimize data storage and processing performance in Azure environments through effective design and configuration.

6. Integration with Azure Services: Understanding of integrating data solutions with other Azure services such as Azure Machine Learning, Azure IoT Hub, and Azure Event Hubs.