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Data Engineering on Google Cloud Platform Training
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Drive Team Excellence with Data Engineering on Google Cloud Platform Corporate Training

Empower your teams with expert-led on-site, off-site, and virtual Data Engineering on Google Cloud Platform Training through Edstellar, a premier corporate training provider for organizations globally. Designed to meet your specific training needs, this group training program ensures your team is primed to drive your business goals. Help your employees build lasting capabilities that translate into real performance gains.

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.

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Key Skills Employees Gain from instructor-led 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 Pipeline Design is the process of creating systems for efficiently moving and transforming data. This skill is important for data engineers and analysts to ensure accurate, timely insights.
  • Data Lake Architecture
    Data Lake Architecture involves designing and managing scalable storage systems for vast amounts of structured and unstructured data. This skill is important for data engineers and architects, as it enables efficient data processing, analytics, and decision-making in organizations.
  • Data Warehousing
    Data Warehousing is the process of collecting, storing, and managing large volumes of data for analysis. This skill is important for data analysts and business intelligence roles, as it enables informed decision-making through efficient data retrieval and reporting.
  • Batch Data Pipelines
    Batch Data Pipelines involve the automated processing of large data sets at scheduled intervals. This skill is important for data engineers and analysts to ensure efficient data management, timely insights, and informed decision-making.
  • Apache Spark
    Apache Spark is an open-source distributed computing system for big data processing. This skill is important for data engineers and data scientists to efficiently analyze large datasets, enabling faster insights and decision-making.
  • Serverless Data Processing
    Serverless Data Processing is the ability to manage and analyze data without server management. this skill is important for data engineers and analysts to enhance scalability, reduce costs, and streamline workflows.

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

Upon completing Edstellar’s Data Engineering on Google Cloud Platform workshop, employees will gain valuable, job-relevant insights and develop the confidence to apply their learning effectively in the professional environment.

  • 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 Group Training with Instructor-led Face to Face and Virtual Options

Attending our Data Engineering on Google Cloud Platform group training classes provides your team with a powerful opportunity to build skills, boost confidence, and develop a deeper understanding of the concepts that matter most. The collaborative learning environment fosters knowledge sharing and enables employees to translate insights into actionable work outcomes.

  • 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

Topics and Outline of Data Engineering on Google Cloud Platform Training

Our virtual and on-premise Data Engineering on Google Cloud Platform training curriculum is structured into focused modules developed by industry experts. This training for organizations provides an interactive learning experience that addresses the evolving demands of the workplace, making it both 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

Who Can Take the Data Engineering on Google Cloud Platform Training Course

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

  • Data Engineers
  • Cloud Engineers
  • Data Analysts
  • Software Developers
  • System Architects
  • Technical Support Engineers
  • IT Administrators
  • Database Administrators
  • DevOps Engineers
  • Site Reliability Engineers
  • Application Developers
  • Managers

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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Delivering Training for Organizations across 100 Countries and 10+ Languages

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

At Edstellar, we understand the importance of impactful and engaging training for employees. As a leading Data Engineering on Google Cloud Platform training provider, we ensure the training is more interactive by offering Face-to-Face onsite/in-house or virtual/online sessions for companies. This approach has proven to be effective, outcome-oriented, and produces a well-rounded training experience for your teams.

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Live Instructor-led Training
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On-site
Face to Face Instructor-led Training
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Off-site
Face to Face Instructor-led Training
Virtual Data Engineering on Google Cloud Platform Training

Edstellar's Data Engineering on Google Cloud Platform virtual/online training sessions bring expert-led, high-quality training to your teams anywhere, ensuring consistency and seamless integration into their schedules.

With global reach, your employees can get trained from various locations
The consistent training quality ensures uniform learning outcomes
Participants can attend training in their own space without the need for traveling
Organizations can scale learning by accommodating large groups of participants
Interactive tools can be used to enhance learning engagement
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On-site Data Engineering on Google Cloud Platform Training

Edstellar's Data Engineering on Google Cloud Platform inhouse face to face instructor-led training delivers immersive and insightful learning experiences right in the comfort of your office.

Higher engagement and better learning experience through face-to-face interaction
Workplace environment can be tailored to learning requirements
Team collaboration and knowledge sharing improves training effectiveness
Demonstration of processes for hands-on learning and better understanding
Participants can get their doubts clarified and gain valuable insights through direct interaction
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Off-site Data Engineering on Google Cloud Platform Training

Edstellar's Data Engineering on Google Cloud Platform offsite face-to-face instructor-led group training offer a unique opportunity for teams to immerse themselves in focused and dynamic learning environments away from their usual workplace distractions.

Distraction-free environment improves learning engagement
Team bonding can be improved through activities
Dedicated schedule for training away from office set up can improve learning effectiveness
Boosts employee morale and reflects organization's commitment to employee development
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        Experienced Trainers

        Our trainers bring years of industry expertise to ensure the training is practical and impactful.

        Quality Training

        With a strong track record of delivering training worldwide, Edstellar maintains its reputation for its quality and training engagement.

        Industry-Relevant Curriculum

        Our course is designed by experts and is tailored to meet the demands of the current industry.

        Customizable Training

        Our course can be customized to meet the unique needs and goals of your organization.

        Comprehensive Support

        We provide pre and post training support to your organization to ensure a complete learning experience.

        Multilingual Training Capabilities

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        Testimonials

        What Our Clients Say

        We pride ourselves on delivering exceptional training solutions. Here's what our clients have to say about their experiences with Edstellar.

        "The Data Engineering on Google Cloud Platform training exceeded my expectations in every way. As a Lead Data Scientist, I gained comprehensive knowledge of practical applications that transformed my practical and immediately applicable. I've successfully implemented these advanced techniques in production environments with measurable impact. The instructor's expertise in expert-led workshops made complex concepts crystal clear and actionable.”

        Darrin Palmer

        Lead Data Scientist,

        Cloud Security Platform Company

        "This Data Engineering on Google Cloud Platform course transformed my approach to professional expertise solutions. The comprehensive modules on hands-on exercises were invaluable for our professional services projects. I can now diverse client requirements. The deep coverage of practical simulations gave me advanced skills I immediately applied to This expertise enabled us to secure a transformative contract with a Fortune 100 organization.”

        Zhang Hua

        Lead Analytics Engineer,

        Enterprise Cloud Services Provider

        "The Data Engineering on Google Cloud Platform training transformed our team's entire approach to technical mastery management and execution. As a Lead Data Warehouse Engineer, the extensive coverage of industry best proven concepts to enhanced capabilities. Our team has automated eighteen critical business processes, reducing manual effort by 70%. Our team's productivity and solution quality have improved measurably, validating this investment.”

        Amr Basel

        Lead Data Warehouse Engineer,

        Cloud Computing Solutions Provider

        “Edstellar’s IT & Technical training programs have been instrumental in strengthening our engineering teams and building future-ready capabilities. The hands-on approach, practical cloud scenarios, and expert guidance helped our teams improve technical depth, problem-solving skills, and execution across multiple projects. We’re excited to extend more of these impactful programs to other business units.”

        Aditi Rao

        L&D Head,

        A Global Technology Company

        Get Your Team Members Recognized with Edstellar’s Course Certificate

        Upon successful completion of the training course offered by Edstellar, employees receive a course completion certificate, symbolizing their dedication to ongoing learning and professional development.

        This certificate validates the employee's acquired skills and is a powerful motivator, inspiring them to enhance their expertise further and contribute effectively to organizational success.

        Certificate of Excellence

        We have Expert Trainers to Meet Your Data Engineering on Google Cloud Platform Training Needs

        The instructor-led 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 Access practices.

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