DP-3011: Implementing a Data Analytics Solution with Azure Databricks
Build big data analytics solutions with Azure Databricks. DP-3011 equips you with the skills to use Apache Spark for data ingestion, transformation, and analysis on a large scale. Learn about cluster management, data processing techniques, and integrating Databricks with other Azure services.
Instructor
DP-3011: Implementing a Data Analytics Solution with Azure Databricks Training
DP-3011: Implementing a Data Analytics Solution with Azure Databricks
The DP-3011: Implementing a Data Analytics Solution with Azure Databricks Course provides in-depth knowledge of Azure Databricks and its integration with Apache Spark and Delta Lake. Participants will learn to provision workspaces, configure SQL Warehouses, and utilize notebooks within Azure Data Factory. This Implementing a Data Analytics Solution with Azure Databricks Training prepares you for practical application in data analytics, helping you harness Microsoft Azure Databricks for robust data solutions. Gain certification and enhance your expertise in Microsoft Data Analytics Solutions with this specialized course.
Target Audience
Data Engineer
Data Scientist
Course Objectives
Introduction to Azure Databricks
Setting Up Azure Databricks Workspaces
Data Ingestion and Processing
Developing Data Pipelines
Data Exploration and Analysis
Machine Learning and AI Integration
Optimizing and Tuning Performance
Security and Compliance
Course Outline
1) Explore Azure Databricks
Provision an Azure Databricks workspace
Identify core workloads and personas for Azure Databricks
Describe key concepts of an Azure Databricks solution
Lab: Explore Azure Databricks
2) 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
Lab: Use Spark in Azure Databricks
3) 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
Lab: Use Delta Lake in Azure Databricks
4) Use SQL Warehouses in Azure Databricks
Create and configure SQL Warehouses in Azure Databricks
Create databases and tables
Create queries and dashboards
Lab: Use a SQL Warehouse in Azure Databricks
5) 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
Lab: Run an Azure Databricks Notebook with Azure Data Factory
The DP-3011: Implementing a Data Analytics Solution with Azure Databricks Course provides in-depth knowledge of Azure Databricks and its integration with Apache Spark and Delta Lake. Participants will learn to provision workspaces, configure SQL Warehouses, and utilize notebooks within Azure Data Factory. This Implementing a Data Analytics Solution with Azure Databricks Training prepares you for practical application in data analytics, helping you harness Microsoft Azure Databricks for robust data solutions. Gain certification and enhance your expertise in Microsoft Data Analytics Solutions with this specialized course.
Target Audience
Data Engineer
Data Scientist
Course Objectives
Introduction to Azure Databricks
Setting Up Azure Databricks Workspaces
Data Ingestion and Processing
Developing Data Pipelines
Data Exploration and Analysis
Machine Learning and AI Integration
Optimizing and Tuning Performance
Security and Compliance
Course Outline
1) Explore Azure Databricks
Provision an Azure Databricks workspace
Identify core workloads and personas for Azure Databricks
Describe key concepts of an Azure Databricks solution
Lab: Explore Azure Databricks
2) 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
Lab: Use Spark in Azure Databricks
3) 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
Lab: Use Delta Lake in Azure Databricks
4) Use SQL Warehouses in Azure Databricks
Create and configure SQL Warehouses in Azure Databricks
Create databases and tables
Create queries and dashboards
Lab: Use a SQL Warehouse in Azure Databricks
5) 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
Lab: Run an Azure Databricks Notebook with Azure Data Factory
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Live Online Training (Duration : 8 Hours)
