TrainingData & analytics / Data & AIDP-750
DP-750Microsoft · authorised trainingLeads to an exam
Implement data engineering solutions using Azure Databricks
This course covers building and maintaining data engineering solutions in Azure Databricks using Unity Catalog, from environment setup to production deployment. Participants learn to secure and govern data, build ingestion and transformation pipelines, and monitor and optimize workloads. The course spans the full lifecycle of an enterprise lakehouse solution on Azure.
- Duration
- 4 days
- Level
- Intermediate
- Provider
- Microsoft
- Topic
- Data & analytics / Data & AI
Course outline
- Learning path: Set up and configure an Azure Databricks environment
- Explore Azure Databricks
- Understand Azure Databricks architecture
- Understand Azure Databricks Integrations
- Select and Configure Compute in Azure Databricks
- Create and organize objects in Unity Catalog
- Learning path: Secure and govern Unity Catalog objects in Azure Databricks
- Secure Unity Catalog objects
- Govern Unity Catalog objects
- Learning path: Prepare and process data with Azure Databricks
- Design and implement data modeling with Azure Databricks
- Ingest data into Unity Catalog
- Cleanse, transform, and load data into Unity Catalog
- Implement and manage data quality constraints with Azure Databricks
- Learning path: Deploy and maintain data pipelines and workloads with Azure Databricks
- Design and implement data pipelines with Azure Databricks
- Implement Lakeflow Jobs with Azure Databricks
- Implement development lifecycle processes in Azure Databricks
- Monitor, troubleshoot and optimize workloads in Azure Databricks
Skills you will gain
- Configuring the Azure Databricks environment and compute resources
- Creating and organizing objects in Unity Catalog
- Securing and governing Unity Catalog objects
- Designing data models and ingestion patterns
- Ingesting, cleansing, and transforming data in Unity Catalog
- Implementing data quality controls
- Designing and implementing data pipelines using lakehouse architecture
- Monitoring, troubleshooting, and optimizing workloads in Azure Databricks
Who should attend
- The target audience is data engineers who have fundamental knowledge of data analytics concepts, a basic understanding of cloud storage, and familiarity with data organization principles
- They should be comfortable working with SQL and have experience using Python, including notebooks, for data engineering tasks
- Learners are expected to have a good understanding of Azure Databricks workspaces and Unity Catalog, along with familiarity with data access patterns and core data engineering and data warehouse concepts
- They should have foundational knowledge of Azure security, including Microsoft Entra ID, and be familiar with Git version control fundamentals
Prerequisites
- Fundamental knowledge of data analytics concepts and cloud storage
- Familiarity with data organization principles
- Comfortable working with SQL
- Experience using Python, including notebooks, for data engineering tasks
- Understanding of Azure Databricks workspaces and Unity Catalog
- Familiarity with data access patterns and core data engineering and data warehouse concepts
- Foundational knowledge of Azure security, including Microsoft Entra ID
- Familiarity with Git version control fundamentals
Certification
Exam
DP-750 - Microsoft Certified: Azure Databricks Data Engineer Associate
This course prepares you for this exam.
4000 PLN
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