Learning Path Overview
This learning path provides a comprehensive guide to leveraging Azure Databricks for handling large-scale data processing and analytics. You'll learn about the core concepts, architecture, and best practices for building robust big data solutions on Azure.
Core Modules
Introduction to Azure Databricks
Understand the fundamentals of Azure Databricks, its architecture, and its role in the big data ecosystem.
Data Ingestion and Preparation
Learn how to ingest data from various sources and prepare it for analysis using Databricks notebooks.
Big Data Processing with Spark
Explore Apache Spark's capabilities within Databricks for distributed data processing and transformation.
Data Warehousing and ETL/ELT
Implement data warehousing strategies and ETL/ELT pipelines using Databricks.
Machine Learning on Databricks
Apply machine learning techniques to your big data using MLflow and Databricks Runtime for Machine Learning.
Optimization and Best Practices
Discover tips and techniques for optimizing performance and implementing best practices for Databricks.