Udemy - Course Cloudera Data Engineer Certification CDP-DE 2026 and Book torrent

Course Cloudera Data Engineer Certification CDP-DE 2026&Book

https://WebToolTip.com

Published 1/2026
Created by HadoopExam Learning Resources
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch
Level: All | Genre: eLearning | Language: English | Duration: 41 Lectures ( 5h 4m ) | Size: 1.66 GB

Exam style Q&A covering Spark on Kubernetes, Apache Airflow, Iceberg, Performance Tuning, Pipelines & Product + eBook

What you'll learn
✓ Design reliable data models on Cloudera Data Platform (CDP) using Apache Iceberg with ACID, time-travel, and schema evolution.
✓ Build and optimize Apache Spark pipelines (DataFrame/Spark SQL) on Kubernetes, with correct executor sizing and shuffle strategy.
✓ Implement incremental ETL/CDC patterns and idempotent upserts using Spark MERGE, checkpoints, and watermarking.
✓ Tune Spark jobs for performance: fix skewed joins, enable AQE, prune partitions/columns, and reduce small files via compaction.
✓ Choose effective partitioning, bucketing, and file-size targets for large fact tables to balance cost and speed.
✓ Orchestrate pipelines with Apache Airflow: production-grade DAG design, retries/SLAs, alerts, and pre/post-load data quality checks.
✓ Secure and operate pipelines on CDP with least-privilege access, secrets management, monitoring dashboards, and auditability.
✓ Deploy and promote jobs via the CDP Data Engineering Service (DES) CLI/API, including blue/green and canary releases.
✓ Diagnose failures quickly from Spark UI and Airflow logs; run safe rollbacks and targeted backfills.
✓ Apply real exam patterns for the CDP Data Engineer certification: topic weightings, common traps, and time-saving strategies.
✓ Map business queries to efficient table formats (Parquet vs Iceberg) and choose the right catalog/integration approach.
✓ Measure success with concrete KPIs: wall-clock time, shuffle MB, task p95, data freshness, and DQ pass rates.

Requirements
● No strict prerequisites — this course is interview-style and exam-focused. You can join as a motivated beginner.
● Basic knowledge of SQL (SELECT, JOIN, GROUP BY) and data warehousing terms. (optional)
● Familiarity with Apache Spark concepts (DataFrames, transformations vs. actions). (optional)
● High-level understanding of Apache Airflow (DAGs, retries, alerts) and CI/CD ideas. (optional)
● Comfort reading technical artifacts like Spark UI screenshots or Airflow logs. (optional)