Descriptions
Azure Databricks and Spark SQL (Python), Databricks is recognised as a leader in the Gartner Magic Quadrant for Data & AI platforms and has become the go-to lakehouse platform for modern data engineering, enabling organisations to build, orchestrate, and optimise pipelines at scale. This course balances theory, hands-on coding, and practical projects: every concept is explained clearly, demonstrated live in Databricks, and reinforced with a multi-phase, end-to-end NYC Taxi project plus downloadable notebooks containing full code, step-by-step documentation, and extra resources. Curriculum highlights include a four-part end-to-end project; foundations (data engineering, Spark architecture, PySpark, and the Lakehouse); Azure setup and Databricks workspace configuration; notebooks and workspace tips; compute topics (clusters, runtimes, serverless vs all-purpose, instance pools, SQL warehouses); Spark SQL (Python) and PySpark transformations; Medallion architecture (Bronze, Silver, Gold); Delta Lake features (transaction log, schema enforcement and evolution, time travel, MERGE/UPDATE/DELETE); workflows and jobs (parameters, failure handling, concurrency, monitoring); Git and local development with VS Code; functions and modularization (Python modules and UDFs); Unity Catalog and governance; streaming and Lakeflow pipelines; performance tuning (explain plans, caching, shuffles, broadcast joins, partitioning, Z-ORDER, Liquid Clustering); and automation & CI/CD. By the end of the course you’ll have the knowledge and confidence to design, build, and optimise production-grade data pipelines on Databricks.
What you’ll learn
- How to use Databricks to build and run data engineering workflows
- The principles of the Lakehouse architecture with Delta Lake
- How to process data with Spark SQL and PySpark
- Best practices for Databricks compute, jobs, and orchestration
- How to apply governance with Unity Catalog and manage secure access
- Working with streaming pipelines using Structured Streaming and Lakeflow
- Applying concepts to real-world projects with modular code and version control
- Real World Scenarios
Who this course is for
- Anyone interested in working with Big Data and Spark
- Anyone interested in working with Databricks
- Anyone interested in working with cloud platforms
- Aspiring Data Engineers
Specificatoin of Azure Databricks and Spark SQL (Python)
- Publisher : Udemy
- Teacher :
- Language: English
- Level : All Levels
- Lectures : 221
- Duration : 17 hours and 29 minutes
Content of Azure Databricks and Spark SQL (Python)
Requirements
- Basic to intermediate SQL
- Basic to intermediate Python
Pictures
Sample Clip
Installation Guide
Extract the files and watch with your favorite player
Subtitle : English
Quality: 720
The 2025/10 version has decreased the number of lessons by 136 and the duration decreased by 12 hours 28 minutes compared to old one.
Download Links
Downloadly
Rapidgator
Password file(s): www.downloadly.ir
File size
6.62 GB
