DP-3011: Implementing a Data Analytics Solution with Azure Databricks
- Duration: 1 Day (8 Hours)
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Overview
Course Details
Prerequisites
DP-3011: Implementing a Data Analytics Solution with Azure Databricks Course Overview
Master big data with DP-3011: gain expertise in Azure Databricks, build complex data pipelines & models, boost your career as a sought-after data pro. Learn from hands-on labs & expert instructors, perfect for data engineers, analysts, scientists & anyone passionate about data! Enroll now & unlock your data’s potential!
Intended Audience
- Data Engineers
- Data Analysts
- Data Scientists
- Database Administrators
- Business Intelligence Developers
- Cloud Solution Architects
- IT Managers and Decision Makers
- Software Developers
- Data Warehouse Developers
- Anyone interested in learning about modern data analytics technologies and tools.
Learning Objectives
- Understand the architecture and key concepts of Azure Databricks and Apache Spark.
- Configure and manage Azure Databricks workspaces and clusters.
- Utilize different data storage options like Azure Data Lake Storage, Azure SQL Data Warehouse, and Azure Cosmos DB.
- Develop batch data processing pipelines using notebooks, libraries, and frameworks like Spark SQL and DataFrames.
- Perform data analysis and transformations using Spark SQL and DataFrames API.
Explore Azure Databricks
- Understand the architecture and key concepts of Azure Databricks and Apache Spark.
- Configure and manage Azure Databricks workspaces and clusters.
- Utilize different data storage options like Azure Data Lake Storage, Azure SQL Data Warehouse, and Azure Cosmos DB.
- Develop batch data processing pipelines using notebooks, libraries, and frameworks like Spark SQL and DataFrames.
- Perform data analysis and transformations using Spark SQL and DataFrames API.
Use Apache Spark in Azure Databricks
- Describe key elements of the Apache Spark architecture.
- Create and configure a Spark cluster.
- Describe use cases for Spark.
- Use Spark to process and analyze data stored in files.
- Use Spark to visualize data.
Use Delta Lake in Azure Databricks
- Describe core features and capabilities of Delta Lake.
- Create and use Delta Lake tables in Azure Databricks.
- Create Spark catalog tables for Delta Lake data.
- Use Delta Lake tables for streaming data.
Use SQL Warehouses in Azure Databricks
- Create and configure SQL Warehouses in Azure Databricks.
- Create databases and tables.
- Create queries and dashboards.
Run Azure Databricks Notebooks with Azure Data Factory
- Describe how Azure Databricks notebooks can be run in a pipeline.
- Create an Azure Data Factory linked service for Azure Databricks.
- Use a Notebook activity in a pipeline.
- Pass parameters to a notebook.
DP-3011: Implementing a Data Analytics Solution with Azure Databricks Course Prerequisites
The prerequisites for the DP-3011: Implementing a Data Analytics Solution with Azure Databricks course typically include:
- Basic understanding of data analytics concepts and techniques.
- Familiarity with cloud computing concepts and Azure services.
- Proficiency in a programming language such as Python or Scala.
- Knowledge of SQL for data querying and manipulation.
- Understanding of data storage and processing technologies such as data lakes and data warehouses.
- Familiarity with Apache Spark concepts and distributed computing principles is beneficial but not mandatory.
- Prior experience with Microsoft Azure services is helpful but not required.
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