DP-3011 Implementing a Data Analytics Solution with Azure Databricks
This one-day course covers analytics on Azure Databricks: explore the platform, analyse data, use Apache Spark, manage data with Delta Lake, build Lakeflow Declarative Pipelines and deploy workloads with Lakeflow Jobs.
About this course
This one-day course covers analytics on Azure Databricks: explore the platform, analyse data, use Apache Spark, manage data with Delta Lake, build Lakeflow Declarative Pipelines and deploy workloads with Lakeflow Jobs.
Curriculum
- Get started with Azure Databricks
- Identify Azure Databricks workloads
- Understand key concepts
- Data governance using Unity Catalog and Microsoft Purview
- Module assessment
- Ingest data with Azure Databricks
- Data exploration tools in Azure Databricks
- Data analysis using DataFrame APIs
- Module assessment
- Get to know Spark
- Create a Spark cluster
- Use Spark in notebooks
- Use Spark to work with data files
- Visualize data
- Module assessment
- Get started with Delta Lake
- Create Delta tables
- Implement schema enforcement
- Data versioning and time travel in Delta Lake
- Data integrity with Delta Lake
- Module assessment
- Explore Lakeflow Declarative Pipelines
- Data ingestion and integration
- Real-time processing
- Module assessment
- What are Lakeflow Jobs?
- Understand key components of Lakeflow Jobs
- Explore the benefits of Lakeflow Jobs
- Deploy workloads using Lakeflow Jobs
- Module assessment
Who it's for
Data analysts and engineers comfortable with Python and SQL.
Before you start
- Familiarity with SQL and basic Python
- Working knowledge of Azure fundamentals
- Basic understanding of data engineering or analytics workflows
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