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Catalog / All levels / Google Cloud Professional Data Engineer (GCP-PDE) Certification with 10 Practice Exams
Mammoth Club All levels 24 sections 69 lectures

Google Cloud Professional Data Engineer (GCP-PDE) Certification with 10 Practice Exams

Engineer the future of data on Google Cloud Platform by mastering big data pipelines and processing.

Created by Team Mammoth
01
Skill level
All levels
02
Sections
24
03
Lectures
69
04
Instructor
Team Mammoth
What's inside

This course includes.

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24
Sections
✓
69
Lectures
✓
52
Resources
✓
13
Quizzes
✓
Certificate of completion
Included
✓
Mobile and desktop access
Included
✓
AI learning assistance
Included
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Course content

Curriculum & lectures.

14 sections · 59 lectures
+ Welcome! 1 lecture
Submit a Question / Feedback Locked
+ 01 Introduction to data engineering 6 lectures
01. Data engineer role Locked
02. Introduction to BigQuery Locked
03. Data lakes and warehouses Locked
04. Transactional databases vs data warehouses Locked
05. Manage data access and production Locked
Quiz - Data Engineering Locked
+ 02 Building a data lake 6 lectures
01 Data storage and ETL options on Google Cloud Locked
02 Building a data lake with Cloud Storage Locked
03 Secure Cloud Storage Locked
04 Storing different data types Locked
05 Cloud SQL as a relational data lake Locked
Quiz - Data Lake Locked
+ 03 Building a data warehouse 7 lectures
01 Building a data warehouse Locked
02 BigQuery for data warehouses Locked
03 Load data into BigQuery Locked
04 Schema design in BigQuery Locked
05 Example case scenario - Nested and repeated fields Locked
06 Optimize with partitioning and clustering Locked
Quiz - Data Warehouse Locked
+ 04 Managing and Securing Dataflow Operations 6 lectures
01 Beam Portability Locked
02 Separate Compute and Storage with Dataflow Locked
03 Dataflow Identity Access Management Locked
04 Google Cloud Dataflow Quotas Locked
05 Enhance security while running Dataflow Locked
06 Dataflow security features Locked
+ 05 Essentials of Data Integration Techniques 4 lectures
01 EL, ELT and ETL Locked
02 Build BigQuery Operations Locked
03 Using E-T-L Locked
04 Solve data quality issues with ETL Locked
+ 06 Optimize Big Data Processing with Hadoop and Spark on Dataproc 8 lectures
01 From Traditional Databases to Hadoop and Spark Ecosystems Locked
02 Run Hadoop on Dataproc Locked
03 Cloud Storage vs Hadoop Locked
04 Optimize Dataproc Locked
05 Optimize Dataproc Storage Locked
06 Optimize Dataproc templates and autoscaling Locked
07 Optimize Dataproc monitoring Locked
Flashcards - Optimize Big Data Processing with Hadoop and Spark on Dataproc Locked
+ 07 Building Robust Data Processing Pipelines with Dataflow 7 lectures
01 Using Dataflow Locked
02 How Dataflow works Locked
03 Creating Dataflow pipelines with Python programming Locked
04 Designing a Dataflow pipeline Locked
05 Transform data with PTransforms Locked
06 Side inputs and windows of data Locked
07 Creating and re-using pipeline templates Locked
+ 08 Managing Pipelines with Cloud Data Fusion and Composer 3 lectures
01 What is Cloud Data Fusion Locked
02 Components of Cloud Data Fusion Locked
03 Coordinate tasks across Cloud with Composer Locked
+ 09 Process Streaming Data with PubSub 2 lectures
01 Process streaming data Locked
02 Push and Pull in PubSub Locked
+ 10 Manage Streaming Data with Dataflow 3 lectures
01 Streaming data challenges Locked
02 Dataflow windowing Locked
Mindmap - Manage Streaming Data with Dataflow Locked
+ 11 Data Streaming, Integration, and Optimization with BigQuery and Bigtable 2 lectures
01 Streaming into BigQuery and visualizing results Locked
02 Optimize Bigtable performance Locked
+ 12 Optimizing Analytics and Cost Management in BigQuery 3 lectures
01 Analytic window functions Locked
02 Best practices for BigQuery Performance Locked
03 Manage BigQuery costs Locked
+ Where to find your exam 1 lecture
Find Your Exams Locked
Description

About this course.

It's time for a career refresh. This comprehensive course will guide you through every aspect of data engineering on Google Cloud, from building data lakes to optimizing big data processing. You’ll gain hands-on experience with key Google Cloud tools and technologies like BigQuery, Dataflow, Cloud Composer, and more.

Introduction to Data Engineering: Learn the key roles and responsibilities of a Data Engineer and get an overview of essential data services like BigQuery, Data Lakes, and Data Warehouses.

Building a Data Lake: Understand how to build and secure a data lake with Cloud Storage, and manage different data types using Cloud SQL as a relational data lake.

Building a Data Warehouse: Learn to design a Data Warehouse using BigQuery, optimize performance with partitioning and clustering, and load data efficiently.

Managing Dataflow Operations: Master Dataflow, Identity Access Management (IAM), and learn how to scale, optimize, and secure data processing pipelines.

Big Data Processing: Optimize Hadoop and Spark on Dataproc for large-scale data processing, and build robust data pipelines for real-time analytics using Dataflow.

Cloud Data Integration: Learn ETL, ELT, and data quality techniques to ensure smooth data integration into BigQuery.

Real-World Labs: Build and test your skills with hands-on labs covering everything from data discovery to cloud storage and cloud SQL.

Don’t miss your chance to gain expertise in Google Cloud Data Engineering. Enroll now and earn your certification! 

Instructors

Taught by people who ship.

Team Mammoth

Team Mammoth

Instructor

Produced by a team of Mammoth Club industry experts. Over 14 years, Mammoth Club has built a global student community in 190+ countries with 9+ million courses sold, releasing over 1,000+ courses and 5,000+ hours of video content.

Ready to start building?

Engineer the future of data on Google Cloud Platform by mastering big data pipelines and processing.

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