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Item number: 154473613

Google Professional Data Engineer Training

Item number: 154473613

Google Professional Data Engineer Training

179,00 216,59 Incl. tax

Order now and start the best online E-Learning Google Professional Data Engineer today. 365 days of training when it suits you.

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Google Professional Data Engineer 2024 E-Learning

Order this unique Google Professional Data Engineer 2024 E-Learning course online!
✔️ 1 year 24/7 access to rich interactive videos, voice, progress monitoring through reports and chapter-by-chapter tests to test your knowledge instantly.

Why choose this course?

The role of a Google Professional Data Engineer is increasingly important in a world that revolves around data. This course is designed to provide professionals with the knowledge and skills needed to drive data-driven decisions, design reliable data solutions and make the most of Google Cloud technologies.

This course:

  • Helps you become familiar with the architecture and security of Google Cloud services.
  • Gives you insight into designing, implementing and managing data solutions.
  • Prepares you for the Google Professional Data Engineer certification exam.

With practical demonstrations and hands-on exercises, this course offers a comprehensive learning method that takes your expertise to the next level.

Who should participate?

This course is perfect for:

  • Data Engineers who want to improve their skills in working with Google Cloud.
  • IT professionals responsible for developing and managing data infrastructures.
  • Big Data specialists who want to harness the power of Google Cloud technology to gain insights.
  • Organisations looking to certify their teams to foster a data-driven culture.

Whether you are a beginner in Google Cloud technologies or want to refine your skills, this course provides valuable insights and practical knowledge.

Course content

This e-learning collection contains 15courses (20 hours +).

1. Designing data processing systems

In this track, the focus will be on what it takes to become a Google Cloud Data Engineer, navigating the Google Cloud platform, building data structures, and planning data pipelines.
Courses:

GCP Data Engineer Pro: Becoming a Google Cloud Data Engineer

Course: 39 Minutes

  • Course Overview
  • The Role of Data Engineer
  • Planning for the Professional Data Engineer Exam3
  • Data Engineer vs. Other Cloud Roles
  • Data Types and Storage
  • Data Processing
  • Data Analysis
  • Machine Learning
  • Mapping Requirements to Architecture
  • Course Summary

GCP Data Engineer Pro: Navigating the Google Cloud Platform

Course: 1 Hour, 5 Minutes

  • Course Overview
  • Basic Google Cloud Platform (GCP) Services
  • Regions and Zones
  • Defining Identity with IAM Roles, Users, Service Accounts, and Policies
  • Creating a Free Tier GCP Account
  • The Google Cloud Console and gcloud CLI
  • Setting Up Core Identity and Access Elements in Google Cloud
  • Managing with the Google Cloud Console
  • Managing with the gcloud CLI
  • Cloud Key Management Service (KMS) on GCP
  • Creating Cloud KMS Key Rings and Symmetric Encryption Keys
  • Course Summary

GCP Data Engineer Pro: Building Robust Data Structures

Course: 1 Hour, 24 Minutes

  • Course Overview
  • Data Storage Architectures
  • Designing the Data Model for a Data Warehouse
  • Data Normalization in a Data Warehouse
  • Data Access Defines Data Warehouse Architecture
  • Discovering Data for a Google Cloud Platform (GCP) Data Lake
  • Best Practices for Cost Control to a GCP Data Lake
  • Best Practices for Access to a GCP Data Lake
  • Processing Data in a Data Lake
  • Monitoring on GCP
  • Building a Data Mesh on GCP
  • Building Governance for a GCP Data Mesh
  • ELT and ETL
  • Course Summary

GCP Data Engineer Pro: Creating a Pipeline of Services

Course: 1 Hour, 12 Minutes

  • Course Overview
  • Data Pipeline Structure
  • Google Data Storage Services
  • Google Data Ingestion Services
  • Hadoop and Hadoop Distributed File System (HDFS)
  • Apache Kafka
  • Google Batch Data Processing
  • Google Streaming Data Processing
  • Apache Beam
  • Google BigQuery
  • MapReduce and Apache Spark
  • Google Vertex AI
  • Course Summary

2. Ingesting and processing the data

In this track, the focus will be on unstructured and structured data, data storage, and BigQuery data warehouse.
Courses:

GCP Data Engineer Pro: Google Cloud Unstructured Data

Course: 1 Hour, 41 Minutes

  • Course Overview
  • Unstructured Data Storage Options
  • Google Cloud Storage
  • Choosing Storage Classes
  • Choosing Bucket Locations
  • Cloud Storage Management
  • Configuring Cloud Storage
  • Object Lifecycle Management
  • Object Security with Access Control
  • Google Persistent Disk
  • Google Filestore
  • Google Memorystore for Redis
  • Data Transfer Services
  • Google Cloud Storage Pricing
  • Unstructured Data Service Pricing
  • Google Cloud Storage Troubleshooting
  • Filestore Troubleshooting
  • Course Summary

GCP Data Engineer Pro: Google Cloud OLTP Structured Data Storage

Course: 2 Hours, 1 Minute

  • Course Overview
  • Cloud SQL Overview
  • Choosing the Best Cloud SQL Edition
  • Core Management Tasks in Cloud SQL
  • Provisioning Cloud SQL Instances
  • Creating Databases on Cloud SQL
  • Creating High Availability on Cloud SQL
  • Recovering from Failure on Cloud SQL
  • Migration to Google Cloud SQL
  • Google Cloud Spanner
  • Provisioning a Spanner Instance, Database, and Schema
  • Defining Cloud Spanner Schema and Adding Data
  • Pricing Out Structured Data Services
  • Troubleshooting Cloud SQL
  • Troubleshooting Cloud Spanner
  • Course Summary

GCP Data Engineer Pro: Google Cloud Semi-structured Data

Course: 1 Hour, 51 Minutes

  • Course Overview
  • Firebase Mobile NoSQL
  • Firebase Realtime Database
  • Provisioning a Realtime Database in Firestore
  • Indexed NoSQL with Firestore
  • Firestore Data models
  • Creating a Firestore Database
  • Using Cloud Bigtable
  • Bigtable Schema Design
  • Provision a BigTable Instance
  • Create a Bigtable Table
  • Creating and Defining Data Storage in Bigtable
  • Loading and Querying Data in Bigtable
  • Pricing Out Semi-structured Data Services
  • Troubleshooting Firebase
  • Troubleshooting BigTable
  • Course Summary

GCP Data Engineer Pro: BigQuery Data Warehouse

Course: 1 Hour, 57 Minutes

  • Course Overview
  • BigQuery Introduction
  • Viewing BigQuery Data Public Datasets
  • Navigating the BigQuery User Interface (UI) and Command Line Interface (CLI)
  • Replication Options for Datasets in BigQuery
  • Creating a Dataset
  • BigQuery Tables and Views
  • BigQuery Routines
  • BigQuery Connections
  • BigQuery Search and Vector Indexes
  • Import Data into BigQuery
  • Options to Batch Load Data into BigQuery
  • Dataset Publishing for Sharing
  • Pricing Models and BigQuery Cost Optimization
  • Looker and Looker Studio
  • Creating Reports in Looker
  • Report Sharing from Looker
  • Looker Pricing
  • BigQuery Troubleshooting
  • Looker Troubleshooting
  • Course Summary

3. Storing the data

In this track, the focus will be on using Google data stream, messaging, dataset processing, and exploring machine learning and AI with Google.
Courses:

GCP Data Engineer Pro: Messaging with Pub/Sub

Course: 59 Minutes

  • Course Overview
  • Cloud Pub/Sub
  • Cloud Pub/Sub vs. Pub/Sub Lite
  • Cloud Pub/Sub Procedures
  • Advanced Pub/Sub Procedures
  • Pub/Sub Schemas
  • Pub/Sub Client Libraries
  • Configuring Cloud Pub/Sub
  • Streaming Data through Pub/Sub to BigQuery
  • Troubleshooting Pub/Sub
  • Course Summary

GCP Data Engineer Pro: Using Google Datastream

Course: 50 Minutes

  • Course Overview
  • Datastream
  • Datastream Sources and Destinations
  • Network Controls for Datastream
  • Creating Connection Profiles
  • Stream Life Cycle and Management Steps
  • Configuring Near Real-time Replication with Datastream
  • Streaming Changes with DataStream to a Storage Bucket
  • Datastream Pricing
  • Datastream Troubleshooting
  • Course Summary

GCP Data Engineer Pro: Dataset Processing

Course: 2 Hours, 15 Minutes

  • Course Overview
  • Comparing Google Cloud Dataproc, Dataprep, Dataflow, and Data Fusion
  • Dataproc Cluster Options
  • Creating a Dataproc Cluster and Running a Spark Job
  • Dataprep Flows
  • Profile, Transform, and Sample Data
  • Using Dataprep
  • Google Cloud Dataflow
  • Building a Dataflow Pipeline
  • Deploying a Dataflow Pipeline
  • Dataflow Pipeline Options
  • Google Cloud Data Fusion
  • Data Fusion Setup
  • Data Fusion Management
  • Creating a Data Fusion Pipeline
  • Pricing for Dataproc, Dataflow, Dataprep, and Data Fusion
  • Dataproc Troubleshooting
  • Dataflow Troubleshooting
  • Course Summary

GCP Data Engineer Pro: Google Machine Learning and AI

Course: 1 Hour, 30 Minutes

  • Course Overview
  • Machine Learning Solutions for Business Problems
  • Machine Learning Algorithms
  • The Machine Learning Workflow
  • Google Machine Learning Products
  • Prebuilt Models
  • Implementing a Prebuilt Model
  • Custom Model Training
  • Data Preparation for Machine Learning
  • Training a Model Using Vertex AI
  • Machine Learning Options for BigQuery
  • Troubleshooting Issues in Machine Learning
  • Course Summary

4. Preparing and using data for analysis

In this track, the focus will be on optimizing, monitoring, and troubleshooting data warehouses, and you will also explore data migrations.
Courses:

GCP Data Engineer Pro: Optimizing a Google Data Warehouse

Course: 1 Hour

  • Course Overview
  • Manage Google Cloud Platform (GCP) Costs
  • Database and Smart Analytics Cost Optimization
  • Control Resources in Dataproc Clusters
  • Pipeline Automation with Cloud Composer or Workflows
  • Creating and Running a DAG for Cloud Composer
  • BigQuery Processing Optimization
  • Workload Management for BigQuery
  • Course Summary

GCP Data Engineer Pro: Monitoring and Troubleshooting Data Warehouses

Course: 1 Hour, 3 Minutes

  • Course Overview
  • Troubleshoot and Monitor with Google Cloud Monitoring
  • Troubleshoot and Monitor with Google Cloud Logging
  • Troubleshoot and Monitor with the Google BigQuery Admin Panel
  • Manage Streaming Pipelines for Resiliency
  • Load Balancing Jobs in Multiple Locations
  • Duplicate Data Handling in Streaming Pipelines
  • Data Replication for Cloud SQL8
  • High Availability with Memorystore Redis Clusters
  • Course Summary

GCP Data Engineer Pro: Data Migrations

Course: 59 Minutes

  • Course Overview
  • Data Migration Planning
  • Plan Validation for Migration
  • Database Migration Service
  • Google Transfer Appliance
  • BigQuery Data Transfer Service
  • Integrate Other Services into a Successful Migration
  • Data Migration Validation
  • The Data Validation Tool (DVT)
  • Data Governance Concerns During Data Migration
  • Course Summary

Get started with Google Professional Data Engineer 2024!

✔️ Learn at your own pace with interactive videos and clear explanations.
✔️ Test your knowledge per chapter with exercises and progress reports.
✔️ Prepare optimally for the official Google Professional Data Engineer exam.
✔️ Get a certificate of attendance as proof of your achievement.

Order your course now and start your journey to data mastery today!

Language English
Qualifications of the Instructor Certified
Course Format and Length Teaching videos with subtitles, interactive elements and assignments and tests
Lesson duration 20:26 Hours
Progress monitoring Yes
Access to Material 365 days
Technical Requirements Computer or mobile device, Stable internet connections Web browsersuch as Chrome, Firefox, Safari or Edge.
Support or Assistance Helpdesk and online knowledge base 24/7
Certification Certificate of participation in PDF format
Price and costs Course price at no extra cost
Cancellation policy and money-back guarantee We assess this on a case-by-case basis
Award Winning E-learning Yes
Tip! Provide a quiet learning environment, time and motivation, audio equipment such as headphones or speakers for audio, account information such as login details to access the e-learning platform.

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