course
Implement data engineering solutions using Azure Databricks (DP-750)
Build, secure, and optimize scalable data lakehouse solutions with Azure Databricks and Unity Catalog governance.
Description
Master end-to-end data engineering with Azure Databricks and Unity Catalog. This course moves from foundational setup to production deployment, covering environment configuration and enterprise-grade governance. Learn to build robust ingestion pipelines, implement security with Unity Catalog, and deploy optimized workloads. By the end, you will have the practical skills to implement, secure, and maintain scalable lakehouse solutions that meet rigorous enterprise requirements.
Audience Profile
The target audience is data engineers.
Certification
This course prepares you for the Associate exam DP-750 (Microsoft Certified: Azure Databricks Data Engineer Associate).
Learning Goals
Prior Knowledge
Comfortable working with SQL and Python, including notebooks, for data engineering tasks Foundational understanding of data engineering and data warehouse concepts Basic understanding of Microsoft Azure Familiarity with git version control
Subjects
- Set up and configure an Azure Databricks environment
- Secure and govern Unity Catalog objects in Azure Databricks
- Prepare and process data with Azure Databricks
- Deploy and maintain data pipelines and workloads with Azure Databricks
1. 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
2. Secure and govern Unity Catalog objects in Azure Databricks
- Secure Unity Catalog objects
- Govern Unity Catalog objects
3. 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
4. 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
Schedule
All courses can also be conducted within your organization as customized or incompany training.
Our training advisors are happy to help you provide personal advice or find Incompany training within your organization.
Prior knowledge courses
Follow-up courses
Certification
The knowledge from this training aligns with these certifications.
"This training was immediately applicable to the project"Attendee
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