AZURE DATA BRICKS

Index:

• Introduction to Azure Databricks:

• Understanding the architecture and components of Azure Databricks.

• Setting up Azure Databricks:

• Provisioning and configuring Azure Databricks clusters, including cluster management and configuration settings.

• Data Engineering with Azure Databricks:

• Working with structured and unstructured data using Databricks notebooks, DataFrame APIs, and SQL.

• Data Analysis and Visualization:

• Performing exploratory data analysis (EDA) and visualizing data using tools like Matplotlib, Seaborn, and Databricks visualization libraries.

• Machine Learning with Azure Databricks:

• Building and deploying machine learning models using MLlib, Scikit-learn, and other machine learning libraries integrated with Azure Databricks.

• Integration with Azure Services:

• Integrating Azure Databricks with other Azure services such as Azure Blob Storage, Azure Data Lake Storage, Azure SQL Database, and Azure Synapse Analytics.

• Performance Optimization:

• Best practices for optimizing performance and scalability in Azure Databricks, including tuning Spark configurations and leveraging Delta Lake for data management.

• Security and Compliance:

• Implementing security measures and compliance standards within Azure Databricks, including access controls, encryption, and auditing.

• Monitoring and Troubleshooting:

• Monitoring job performance, diagnosing issues, and troubleshooting common problems in Azure Databricks environments.