Databricks Certified Data Engineer Associate Ultimate CoursePublished 9/2026
Created by Cloud Guru Amit
MP4 |
Video: h264, 1920x1080 |
Audio: AAC, 44.1 KHz, 2 Ch
Level: All Levels |
Genre: eLearning |
Language: English |
Duration: 117 Lectures ( 3h 38m ) |
Size: 1.7 GB
⚡ Explain Lakehouse architecture and Delta Lake basics.
⚡ Identify Databricks compute types, clusters, and cost models.
⚡ Ingest data with Auto Loader, COPY INTO, and Lakeflow Connect.
⚡ Load batch and streaming data into Delta tables.
⚡ Transform data using Spark SQL and PySpark.
⚡ Implement Medallion architecture: Bronze, Silver, Gold layers.
⚡ Apply joins, aggregations, pivots, and window functions.
⚡ Model Slowly Changing Dimensions (SCD) and temporal tables.
⚡ Configure triggers, scheduling, alerts, and retries.
⚡ Monitor pipeline execution with logs and metrics.
⚡ Optimize Delta tables with OPTIMIZE and VACUUM.
⚡ Manage Unity Catalog privileges for users and groups.
⚡ Configure audit logging and lineage tracking in Catalog Explorer.
⚡ Apply ABAC policies and data retention rules for compliance.
Requirements❗ Basic knowledge of SQL and ability to write simple queries.
❗ Familiarity with relational database concepts like tables, views, and schemas.
DescriptionAre you ready to become a
Databricks Certified Data Engineer Associate and gain the skills to design, build, and optimize modern data solutions? This course is your complete pathway - combining
all theory concepts from the official exam syllabus with
real IT company end‑to‑end projects that prepare you for both certification and real‑world success.
You'll start by mastering the
Databricks Lakehouse Platform, Delta Lake fundamentals, and Unity Catalog governance. From there, you'll dive into
data ingestion pipelines using Auto Loader, COPY INTO, and Lakeflow Connect, while applying schema enforcement, partitioning, and optimization strategies.
Next, you'll transform and model data with Spark SQL and PySpark, implementing the
Medallion architecture (Bronze, Silver, Gold layers), joins, aggregations, pivots, and Slowly Changing Dimensions. You'll then orchestrate workflows with
Lakeflow Jobs, configure triggers and alerts, and monitor execution with logs and metrics.
The course also covers
CI/CD best practices with Git, Databricks Asset Bundles, CLI, and REST APIs, ensuring you can deploy and manage pipelines seamlessly. You'll learn to troubleshoot Spark jobs, optimize Delta tables, and integrate with
Azure Monitor for proactive workload management.
Finally, you'll master
security and governance - from Unity Catalog privileges and row‑level security to ABAC policies, lineage tracking, and secure Delta Sharing.
By the end of this course, you'll not only be
exam‑ready for the Databricks Certified Data Engineer Associate certification, but also equipped with
job‑ready skills to design scalable, secure, and cost‑optimized data solutions in real IT environments.
Who this course is for⭐ Database professionals and SQL developers expanding into Databricks and modern data engineering.
⭐ Students and beginners with basic SQL knowledge who want to learn Databricks from zero to certification level.
⭐ Certification aspirants preparing for the Databricks Certified Data Engineer Associate exam.
⭐ BI and analytics professionals integrating Databricks with AI/BI tools for advanced insights.
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