Google Professional Data Engineer (GCP)

The Professional Data Engineer exam enables data-driven decision making by collecting, transforming, and visualizing data. The sole objective of a Google Cloud Certified – Professional Data Engineer is to design, build, maintain, and troubleshoot data processing systems with a particular emphasis on the security, reliability, fault-tolerance, scalability, fidelity, and efficiency of the systems.

Table of Contents

Cloud Basics

• Cloud computing
• Cloud-computing models

GCP Basics

• GCP Services
• Google Cloud Functions

Storage Models

• ER Model
• NoSQL Model
• Google Products and Storage Options
• Big Data Architectures
• Capacity Planning

Data Migration

• Present Environment
• Workload
• Types of migrations
• Google Cloud Adoption Framework
• The migration Process

Data Quality Management

• Validate Data
• Quality metadata
• Auditing

Data Lifecycle

• Ingest
• Store
• Process and analyze
• Explore and visualize
• Orchestration

Schema Design

• What is Schema Design
• Relational Schema Design
• Non-relational Schema Design in Cloud Bigtable
• Table design

Cloud SQL

• Cloud SQL Features
• Importing Data
• Exporting Data
• CloudSQL Instance settings

Datastore

• Datastore Overview
• Data Organization
• Queries
• Indexing
• Data Consistency

Bigtable

• Bigtable Overview
• Cloud Bigtable architecture
• Data Organization
• Load balancing
• Columns
• Supported data types
• Empty cells
• Column qualifiers
• Compactions
• Mutations and deletions
• Data compression
• Data durability
• Security
• Instance Configuration
• Storage types
• Data Management
• cbt tool
• Best Practices

Cloud Spanner

• Cloud Spanner Overview
• Schema and data model
• Cloud Spanner Instances

Cloud Pub/Sub

• Cloud Pub/Sub Overview
• Monitoring

Cloud Dataflow

• Cloud Dataflow Overview
• Key Concepts
• Pipeline Design
• Pipeline Lifecycle, creation and Transform
• Cloud Dataflow templates
• Streaming Pipeline
• Best Practices

Dataproc

• Dataproc Overview
• Configure Dataproc Cluster and Submit Job
• Migrating to Google Cloud
• Best Practices

BigQuery

• BigQuery Overview
• Interacting with BigQuery
• Loading Data
• Exporting Data
• Optimize for Performance and Cost
• Queries
• BigQuery Logging and Monitoring
• BigQuery Best Practices

Google Stackdriver

• Monitoring
• Logging
• Error Reporting
• Debugging
• Tracing

Machine Learning

• What is Machine Learning?
• Inductive Learning
• Machine Learning Algorithms
• Neural Networks

Google AI Platform (Formerly Cloud ML Engine)

• AI Platform Overview
• AI Platform Training
• AI Platform Pipelines

Pre-trained Machine Learning API’s

• Pre-trained ML API’s
• Cloud Vision Product Search
• Vision API
• NL API

Datalab

• Datalab Overview
• Running Datalab

Dataprep

• Dataprep Overview

DataStudio

• DataStudio Basics
• Steps to use the tool

Cloud Composer

• Cloud Composer Overview

Security and Compliance

• Google Security Culture
• Operational Security
• Technology with Security at Its Core
• Independent Third-Party Certifications
• Regulatory compliance
• General Data Protection Regulation (GDPR)
• The Health Insurance Portability and Accountability Act of 1996 (HIPAA)
• Cloud Data Loss Prevention (DLP)
• Encryption Basics
• Cloud Key Management Service

Cloud IAM

• Access management
• Cloud IAM policy
• Cloud IAM working