Corporate Data Engineering on Google Cloud Platform Training Course

Edstellar's Data Engineering on Google Cloud Platform instructor-led training course enables professionals to efficiently leverage GCP's tools, optimize data processes, ensure data quality, and gain a competitive edge in the data-driven business landscape. Empower your team to leverage the power of data engineering for excellence.

32 - 40 hrs
Instructor-led (On-site/Virtual)
Language
English
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Data Engineering on Google Cloud Platform Training
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Data Engineering on Google Cloud Platform Corporate Training Course

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Drive Team Excellence with Data Engineering on Google Cloud Platform Training for Employees

Empower your teams with expert-led on-site/in-house or virtual/online Data Engineering on Google Cloud Platform Training through Edstellar, a premier corporate training company for organizations globally. Our tailored Data Engineering on Google Cloud Platform corporate training course equips your employees with the skills, knowledge, and cutting-edge tools needed for success. Designed to meet your specific needs, this Data Engineering on Google Cloud Platform group training program ensures your team is primed to drive your business goals. Transform your workforce into a beacon of productivity and efficiency.

Data Engineering on Google Cloud Platform Training equips individuals with skills to efficiently collect, store, process, and analyze data using GCP services, covering ingestion, storage, processing, pipeline design, optimization, governance, security, and monitoring. This training enables organizations to leverage Google Cloud services for enhancing decision-making processes, optimizing data workflows, and unlocking the full potential of their data assets to drive organizational growth and innovation.

Edstellar's Data Engineering on the Google Cloud Platform instructor-led training course can be customized to meet an organization's requirements. The virtual/onsite Data Engineering on the Google Cloud Platform training course, led by expert trainers, offers interactive sessions that combine hands-on learning experiences with theoretical knowledge ensuring professionals gain insights to tackle any objectives that arise.

Key Skills Employees Gain from Data Engineering on Google Cloud Platform Training

Data Engineering on Google Cloud Platform skills corporate training will enable teams to effectively apply their learnings at work.

  • Data Pipeline Design
  • Data Lake Architecture
  • Data Warehousing
  • Batch Data Pipelines
  • Apache Spark
  • Serverless Data Processing

Data Engineering on Google Cloud Platform Training for Employees: Key Learning Outcomes

Edstellar’s Data Engineering on Google Cloud Platform training for employees will not only help your teams to acquire fundamental skills but also attain invaluable learning outcomes, enhancing their proficiency and enabling application of knowledge in a professional environment. By completing our Data Engineering on Google Cloud Platform workshop, teams will to master essential Data Engineering on Google Cloud Platform and also focus on introducing key concepts and principles related to Data Engineering on Google Cloud Platform at work.


Employees who complete Data Engineering on Google Cloud Platform training will be able to:

  • Apply data engineering concepts to design robust data pipelines on Google Cloud Platform
  • Implement data lake architectures to efficiently store and manage large volumes of structured and unstructured data
  • Construct data warehouses for optimized storage and retrieval of business-critical information
  • Develop batch data pipelines using industry-standard tools and techniques
  • Execute Apache Spark jobs on Cloud Dataproc for scalable data processing
  • Implement serverless data processing solutions with Cloud Dataflow to handle real-time data streams
  • Manage data pipelines effectively using Cloud Data Fusion and Cloud Composer orchestration tools
  • Utilize advanced analytics and AI services to extract actionable insights from large datasets

Key Benefits of the Data Engineering on Google Cloud Platform Corporate Training

Attending our Data Engineering on Google Cloud Platform classes tailored for corporations offers numerous advantages. Through our on-site/in-house or virtual/online Data Engineering on Google Cloud Platform training classes, participants will gain confidence and comprehensive insights, enhance their skills, and gain a deeper understanding of Data Engineering on Google Cloud Platform.

  • Enables professionals to build custom machine learning models with SQL in BigQuery ML
  • Facilitates the creation of production ML pipelines using Kubeflow for seamless deployment
  • Develops required skills in professionals to execute batch and streaming data processing tasks
  • Equips the team with advanced data engineering techniques for building scalable data pipelines
  • Empowers professionals with the skills to design and implement data lakes and warehouses on GCP
  • Enhances the team's ability to process and analyze large-scale data with Cloud AI Platform Notebooks
  • Provides teams with the insights into leveraging serverless data processing solutions for efficient resource utilization
  • Instills ideas in professionals for effectively managing data pipelines using GCP services like Data Fusion and Composer

Data Engineering on Google Cloud Platform Training Topics and Outline

Our virtual and on-premise Data Engineering on Google Cloud Platform training curriculum is divided into multiple modules designed by industry experts. This Data Engineering on Google Cloud Platform training for organizations provides an interactive learning experience focused on the dynamic demands of the field, making it relevant and practical.

  1. Overview of data engineering
    • Introduction to data engineering concepts
    • Role of data engineers in organizations
  2. Data engineering lifecycle
    • Understanding the data lifecycle stages
    • Importance of data quality and governance
  1. Introduction to Data Lakes
    • Definition and architecture of data lakes
    • Benefits and use cases of data lakes
  2. Implementing Data Lakes
    • Designing data lake architecture
    • Ingesting and storing data in data lakes
  1. Data warehouse concepts
    • Understanding data warehousing principles
    • Data modeling for data warehousing
  2. Implementing data warehouses
    • Designing data warehouse architecture
    • Loading and transforming data in data warehouses
  1. Batch processing overview
    • Understanding batch processing concepts
    • Batch processing vs. real-time processing
  2. Building batch data pipelines
    • Designing batch data pipeline architecture
    • Implementing batch processing workflows
  1. Introduction to Apache Spark
    • Overview of Apache Spark framework
    • Benefits of using Apache Spark for data processing
  2. Spark on Cloud Dataproc
    • Setting up and configuring Spark on Google Cloud Dataproc
    • Running Spark jobs on Cloud Dataproc clusters
  1. Introduction to Cloud Dataflow
    • Overview of serverless data processing
    • Features and capabilities of Cloud Dataflow
  2. Building Data Pipelines with Cloud Dataflow
    • Writing and deploying Dataflow pipelines
    • Monitoring and optimizing Dataflow jobs
  1. Introduction to Cloud Data Fusion
    • Overview of Cloud Data Fusion service
    • Benefits of using Cloud Data Fusion for data integration
  2. Managing Data Pipelines with Cloud Composer
    • Orchestration and scheduling of data pipelines with Cloud Composer
    • Integration with other Google Cloud services
  1. Streaming data concepts
    • Understanding streaming data and event-driven architectures
    • Use cases for streaming data processing
  2. Implementing streaming data pipelines
    • Designing and building streaming data pipelines
    • Real-time data processing with Google Cloud services
  1. Introduction to Cloud Pub/Sub
    • Overview of messaging systems and Cloud Pub/Sub
    • Features and capabilities of Cloud Pub/Sub
  2. Implementing Serverless messaging
    • Creating and managing Pub/Sub topics and subscriptions
    • Integrating Pub/Sub with other Google Cloud services
  1. Advanced features of Cloud Dataflow
    • Windowing and watermarking in streaming data processing
    • Handling late data and out-of-order events
  2. Building streaming Data Pipelines with Dataflow
    • Implementing complex streaming data processing logic
    • Optimizing performance and cost of Dataflow pipelines
  1. Introduction to BigQuery and Bigtable
    • Overview of Google Cloud BigQuery and Bigtable services
    • Use cases for high-throughput streaming data processing
  2. Processing streaming data with BigQuery and Bigtable
    • Configuring and optimizing streaming data ingestion in BigQuery
    • Leveraging Bigtable for real-time data storage and retrieval
  1. Advanced BigQuery features
    • Working with nested and repeated data structures
    • Partitioning and clustering tables for improved performance
  2. Optimizing BigQuery performance
    • Query optimization techniques for faster query execution
    • Monitoring and troubleshooting BigQuery performance issues
  1. Overview of Analytics and AI
    • Introduction to analytics and AI capabilities on Google Cloud
    • Use cases for analytics and AI in data engineering workflows
  2. Integrating analytics and AI services
    • Using AI APIs for text and image analysis
    • Building custom ML models with Google Cloud AI Platform
  1. ML model APIs overview
    • Overview of prebuilt ML model APIs available on Google Cloud
    • Benefits of using prebuilt ML models for unstructured data
  2. Implementing ML Model APIs
    • Integrating ML model APIs into data engineering pipelines
    • Processing unstructured data with ML model APIs
  1. Introduction to AI platform notebooks
    • Overview of AI platform notebooks for collaborative data analysis
    • Features and capabilities of AI platform notebooks
  2. Performing Big Data analytics
    • Analyzing large datasets with AI platform notebooks
    • Visualizing and interpreting analytics results
  1. Introduction to Kubeflow
    • Overview of Kubeflow for building and deploying ML pipelines
    • Use cases for Kubeflow in production ML workflows
  2. Building ML Pipelines with Kubeflow
    • Designing end-to-end ML pipelines with Kubeflow components
      • Deploying and managing ML models in production environments
  1. Introduction to BigQuery ML
    • Overview of BigQuery ML for building ML models using SQL
    • Benefits of using BigQuery ML for model development
  2. Building custom ML models
    • Writing SQL queries to create and train ML models in BigQuery
    • Evaluating and deploying custom ML models for predictive analytics

This Corporate Training for Data Engineering on Google Cloud Platform is ideal for:

What Sets Us Apart?

Data Engineering on Google Cloud Platform Corporate Training Prices

Our Data Engineering on Google Cloud Platform training for enterprise teams is tailored to your specific upskilling needs. Explore transparent pricing options that fit your training budget, whether you're training a small group or a large team. Discover more about our Data Engineering on Google Cloud Platform training cost and take the first step toward maximizing your team's potential.

Small Group
Large Groups

Request for a quote to know about our Data Engineering on Google Cloud Platform corporate training cost and plan the training initiative for your teams. Our cost-effective Data Engineering on Google Cloud Platform training pricing ensures you receive the highest value on your investment.

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Our customized corporate training packages offer various benefits. Maximize your organization's training budget and save big on your Data Engineering on Google Cloud Platform training by choosing one of our training packages. This option is best suited for organizations with multiple training requirements. Our training packages are a cost-effective way to scale up your workforce skill transformation efforts..

Starter Package

125 licenses

64 hours of training (includes VILT/In-person On-site)

Tailored for SMBs

Most Popular
Growth Package

350 licenses

160 hours of training (includes VILT/In-person On-site)

Ideal for growing SMBs

Enterprise Package

900 licenses

400 hours of training (includes VILT/In-person On-site)

Designed for large corporations

Custom Package

Unlimited licenses

Unlimited duration

Designed for large corporations

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Data Engineering on Google Cloud Platform Course Completion Certificate

Upon successful completion of the Data Engineering on Google Cloud Platform training course offered by Edstellar, employees receive a course completion certificate, symbolizing their dedication to ongoing learning and professional development. This certificate validates the employees' acquired skills and serves as a powerful motivator, inspiring them to further enhance their expertise and contribute effectively to organizational success.

Target Audience for Data Engineering on Google Cloud Platform Training Course

The Data Engineering on Google Cloud Platform training course is ideal for data engineers, software engineers, database administrators, and data analysts.

The Data Engineering on Google Cloud Platform training program can also be taken by professionals at various levels in the organization.

Data Engineering on Google Cloud Platform training for managers

Data Engineering on Google Cloud Platform training for staff

Data Engineering on Google Cloud Platform training for leaders

Data Engineering on Google Cloud Platform training for executives

Data Engineering on Google Cloud Platform training for workers

Data Engineering on Google Cloud Platform training for businesses

Data Engineering on Google Cloud Platform training for beginners

Data Engineering on Google Cloud Platform group training

Data Engineering on Google Cloud Platform training for teams

Data Engineering on Google Cloud Platform short course

Prerequisites for Data Engineering on Google Cloud Platform Training

Professionals with a basic understanding of data engineering concepts and principles can take up the Data Engineering on Google Cloud Platform training course.

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Bringing you the Best Data Engineering on Google Cloud Platform Trainers in the Industry

The instructor-led Data Engineering on Google Cloud Platform training is conducted by certified trainers with extensive expertise in the field. Participants will benefit from the instructor's vast knowledge, gaining valuable insights and practical skills essential for success in Data Engineering on Google Cloud Platform Access practices.

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Training Delivery Modes for Data Engineering on Google Cloud Platform Group Training

At Edstellar, we understand the importance of impactful and engaging training for employees. To ensure the training is more interactive, we offer Face-to-Face onsite/in-house or virtual/online Data Engineering on Google Cloud Platform training for companies. This method has proven to be the most effective, outcome-oriented and well-rounded training experience to get the best training results for your teams.

Virtuval
Virtual

Instructor-led Training

Engaging and flexible online sessions delivered live, allowing professionals to connect, learn, and grow from anywhere in the world.

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On-Site
On-Site

Instructor-led Training

Customized, face-to-face learning experiences held at your organization's location, tailored to meet your team's unique needs and objectives.

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Off-Site
Off-site

Instructor-led Training

Interactive workshops and seminars conducted at external venues, offering immersive learning away from the workplace to foster team building and focus.

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