Building Modern Data Applications Using Databricks Lakehouse
Develop, optimize, and monitor data pipelines on Databricks
Created by Will Girten
Explore how to build, optimize, and monitor scalable data pipelines using Databricks Lakehouse. You will learn to manage real-time data, automate workflows, and ensure data quality and security, all while streamlining your data engineering tasks.
Packt | Oct 2024 | 246 min
What You Will Learn
You will start by understanding the core features of Databricks Lakehouse, then move on to hands-on practice with Delta Live Tables and the medallion architecture. As you progress, you will set up data validation, automate deployments, and use monitoring tools to control performance and costs. Each step builds practical skills for modern data engineering.
Key Features
- Build and automate real-time data pipelines using Delta Live Tables and workflows
- Monitor, validate, and secure data with Unity Catalog and robust governance tools
- Optimize deployment and manage costs by integrating CI/CD practices with Databricks
Target Audience
Ideal for data engineers and analysts who already know Python and Apache Spark and want to streamline data ingestion, transformation, and orchestration. If your goal is to automate pipeline deployment, improve data governance, or manage lakehouse data for analytics and reporting, you will gain actionable skills and confidence here.
