Data Engineer Career Path By Microsoft - DP900 to DP 203

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Data Engineer Career Path By Microsoft - DP900 to DP 203 von Mind Map: Data Engineer Career Path  By Microsoft - DP900 to DP 203

1. 1 Get started with data engineering on Azure

1.1. Introduction to data engineering on Azure

1.2. Introduction to Azure Data Lake Storage Gen2

1.3. Introduction to Azure Synapse Analytics

2. Build data analytics solutions using Azure Synapse serverless SQL pools

2.1. Use Azure Synapse serverless SQL pool to query files in a data lake

2.2. Use Azure Synapse serverless SQL pools to transform data in a data lake

2.3. Create a lake database in Azure Synapse Analytics

2.4. Secure data and manage users in Azure Synapse serverless SQL pools

3. Perform data engineering with Azure Synapse Apache Spark Pools

3.1. Analyze data with Apache Spark in Azure Synapse Analytics

3.2. Transform data with Spark in Azure Synapse Analytics

3.3. Use Delta Lake in Azure Synapse Analytics

4. Work with Data Warehouses using Azure Synapse Analytics

4.1. Analyze data in a relational data warehouse

4.2. Load data into a relational data warehouse

4.3. Manage and monitor data warehouse activities in Azure Synapse Analytics

4.4. Analyze and optimize data warehouse storage in Azure Synapse Analytics

4.5. Secure a data warehouse in Azure Synapse Analytics

5. Azure Data Fundamentals DP-900

5.1. Explore Core data Concepts

5.1.1. Explore core data concepts

5.1.2. Explore data roles and services

5.2. Explore Relational data in Azure

5.2.1. Explore fundamental relational data concepts

5.2.2. Explore relational database services in Azure

5.3. Explore non- relational data in Azure

5.3.1. Explore Azure Storage for non-relational data

5.3.2. Explore fundamentals of Azure Cosmos DB

5.4. Explore data Analytics in Azure

5.4.1. Explore fundamentals of large-scale data warehousing

5.4.2. Explore fundamentals of real-time analytics

5.4.3. Explore fundamentals of data visualization

6. Transfer and transform data with Azure Synapse Analytics pipelines

6.1. Build a data pipeline in Azure Synapse Analytics

6.2. Use Spark Notebooks in an Azure Synapse Pipeline

7. Work with Hybrid Transactional and Analytical Processing Solutions using Azure Synapse Analytics

7.1. Plan hybrid transactional and analytical processing using Azure Synapse Analytics

7.2. Implement Azure Synapse Link with Azure Cosmos DB

7.3. Implement Azure Synapse Link for SQL

8. Implement a Data Streaming Solution with Azure Stream Analytics

8.1. Get started with Azure Stream Analytics

8.2. Ingest streaming data using Azure Stream Analytics and Azure Synapse Analytics

8.3. Visualize real-time data with Azure Stream Analytics and Power BI

9. Govern data across an enterprise

9.1. Introduction to Microsoft Purview

9.2. Discover trusted data using Microsoft Purview

9.3. Catalog data artifacts by using Microsoft Purview

9.4. Manage Power BI assets by using Microsoft Purview

9.5. Integrate Microsoft Purview and Azure Synapse Analytics

10. Data engineering with Azure Databricks

10.1. Explore Azure Databricks

10.2. Use Apache Spark in Azure Databricks

10.3. Use Delta Lake in Azure Databricks

10.4. Use SQL Warehouses in Azure Databricks

10.5. Run Azure Databricks Notebooks with Azure Data Factory