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Overview

This 2-day course introduces learners to Google Cloud’s data integration capability using Cloud Data Fusion. In this course, we discuss challenges with data integration and the need for a data integration platform (middleware). We then discuss how Cloud Data Fusion can help to effectively integrate data from a variety of sources and formats and generate insights. We take a look at Cloud Data Fusion’s main components and how they work, how to process batch data and real time streaming data with visual pipeline design, rich tracking of metadata and data lineage, and how to deploy data pipelines on various execution engines.
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What You'll Learn

  • Identify the need of data integration,
  • Understand the capabilities Cloud Data Fusion provides as a data integration platform,
  • Identify use cases for possible implementation with Cloud Data Fusion,
  • List the core components of Cloud Data Fusion,
  • Design and execute batch and real time data processing pipelines,
  • Work with Wrangler to build data transformations
  • Use connectors to integrate data from various sources and formats,
  • Configure execution environment; Monitor and Troubleshoot pipeline execution,
  • Understand the relationship between metadata and data lineage

Who Should Attend

This course is primarily intended for the following participants:

  • Data Engineer
  • Data Analysts
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Prerequisites

To get the most out of this course, participants are encouraged to have:

  • Completed “Introduction to Data Engineering”

Learning Journey

Coming Soon...

Module 01: Introduction to data integration and Cloud Data Fusion

  • Data integration: what, why, challenges
  • Data integration tools used in industry
  • User personas
  • Introduction to Cloud Data Fusion
  • Data integration critical capabilities
  • Cloud Data Fusion UI components

Module 02: Building pipelines

  • Cloud Data Fusion architecture
  • Core concepts
  • Data pipelines and directed acyclic graphs (DAG)
  • Pipeline Lifecycle
  • Designing pipelines in Pipeline Studio

Module 03: Designing complex pipelines

  • Branching, Merging and Joining
  • Actions and Notifications
  • Error handling and Macros
  • Pipeline Configurations, Scheduling, Import and Export

Module 04: Pipeline execution environment

  • Schedules and triggers
  • Execution environment: Compute profile and provisioners
  • Monitoring pipelines

Module 05: Building Transformations and Preparing Data with Wrangler

  • Wrangler
  • Directives
  • User-defined directives

Module 06: Connectors and streaming pipelines

  • Understand the data integration architecture.
  • List various connectors.
  • Use the Cloud Data Loss Prevention (DLP) API.
  • Understand the reference architecture of streaming pipelines.
  • Build and execute a streaming pipeline.

Module 07: Metadata and data lineage

  • Metadata
  • Data lineage

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Frequently Asked Questions (FAQs)

  • Why get Google Cloud Platform (GCP) certified?

    Google Cloud certifications validate your expertise in cloud technologies and your proficiency in using Google Cloud Platform's vast array of services.

    These certifications are recognized globally and highly sought after by employers, as they demonstrate your ability to design, develop, and manage scalable and secure cloud solutions on GCP.

    Google Cloud-certified professionals are in high demand, opening doors to new career opportunities and higher earning potential.

  • What to expect for the examination?

    Google Cloud offers a variety of certification exams across different levels (Foundational, Associate, and Professional) covering various job roles and specializations.

    The exams typically consist of multiple-choice and multiple-select questions, as well as scenario-based questions that assess your ability to apply your knowledge in real-world situations.

    Note: Certification requirements and policies may be updated by Google Cloud from time to time. We apologize for any discrepancies; do get in touch with us if you have any questions.

  • How long is Google Cloud Platform (GCP) certification valid for?

    Most Google Cloud certifications, including Professional-level certifications, are valid for two years from the date of passing the exam.

    The Cloud Digital Leader and Associate Cloud Engineer certifications are valid for three years from the date of passing the exam.

    To maintain your certification, you will need to recertify by passing the latest version of the same exam or an equivalent higher-level certification exam before your current certification expires.

    You will receive a notification from Google Cloud prior to your certification's expiration date.

    Note: Certification requirements and policies may be updated by Google Cloud from time to time. We apologize for any discrepancies; do get in touch with us if you have any questions.

  • Why take this course with Trainocate?

    Here’s what sets us apart:

    - Global Reach, Localized Accessibility: Benefit from our geographically diverse training hubs in 24 countries (and counting!).

    - Top-Rated Instructors: Our team of subject matter experts (with high average CSAT and MTM scores) are passionate to help you accelerate your digital transformation.

    - Customized Training Solutions: Choose from on-site, virtual classrooms, or self-paced learning to fit your organization and individual needs.

    - Experiential Learning: Dive into interactive training with our curated lesson plans. Participate in hands-on labs, solve real-world challenges, and take on comprehensive assessments.

    - Learn From The Best: With 30+ authorized training partnerships and countless awards from Microsoft, AWS, Google – you're guaranteed learning from the industry's elite.

    - Your Bridge To Success: We provide up-to-date course materials, helpful exam guides, and dedicated support to validate your expertise and elevate your career.

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Course Curriculum

Course Curriculum

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Training Schedule

Exam & Certification

Exam & Certification

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Frequently Asked Questions

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