Course Overveiw

This brand-new associate-level certification exam is intended for individuals new to securing and managing data on Google Cloud. This exam focuses on practical skills using Google Cloud tools and services to perform tasks such as data cleaning, data transformation, data analysis, and data visualization. The Associate Data Practitioner exam is designed to be an entry point to Google Cloud’s portfolio of data certifications which include the Professional Machine Learning and Professional Data Engineer certifications.

After completing this course, students will be able to:

  • Differentiate between different data manipulation methodologies (e.g., ETL, ELT, ETLT).
  • Choose the appropriate data transfer tool.
  • Assess data quality.
  • Conduct data cleaning (e.g., Cloud Data Fusion, BigQuery, SQL, Dataflow).
  • Distinguish the format of the data.
  • Choose the appropriate extraction tool (e.g., Dataflow, BigQuery Data Transfer Service, Database Migration Service, Cloud Data Fusion).
  • Load data into Google Cloud storage systems using the appropriate tool.
  • Define and execute SQL queries in BigQuery to generate reports and extract key insights.
  • Use Jupyter notebooks to analyze and visualize data.
  • Analyze data to answer business questions.
  • Create, modify, and share dashboards to answer business questions.
  • Compare Looker and Looker Studio for different analytics use cases.
  • Manipulate simple LookML parameters to modify a data model.
  • Identify ML use cases for developing models by using BigQuery ML and AutoML.
  • Plan a standard ML project.
  • Execute SQL to create, train, and evaluate models using BigQuery ML.
  • Organize models in Model Registry.
  • Evaluate use cases for ELT and ETL.
  • Monitor Dataflow pipeline progress using the Dataflow job UI.
  • Review and analyze logs in Cloud Logging and Cloud Monitoring.
  • Compare methods of access control for Cloud Storage.
  • Determine when to share data using Analytics Hub.
  • Distinguish between primary and secondary data storage location type for data redundancy.
  • Identify use cases for customer-managed encryption keys (CMEK), customer-supplied encryption keys (CSEK), and Google-managed encryption keys (GMEK).
  • Understand the role of Cloud Key Management Service (Cloud KMS) to manage encryption keys.
  • Identify the difference between encryption in transit and encryption at rest.

Upcoming Batches

Loading Dates...

Key features of Introduction to Associate Data Practitioner.

  • Data Fundamentals

    • Understanding basic concepts of structured and unstructured data.
    • Knowledge of relational databases and SQL.
    • Familiarity with data formats such as CSV, JSON, and Parquet.

  • GCP Services for Data Management

    • BigQuery: Basics of setting up and querying data warehouses.
    • Cloud Storage: Storing, retrieving, and managing data in buckets.
    • Cloud SQL: Working with managed databases like MySQL and PostgreSQL.
    • Dataflow: Introduction to data pipelines for ETL/ELT tasks.
    • Pub/Sub: Basics of message-driven architectures and event streaming.

  • Data Analysis and Insights

    • Creating and running simple queries in BigQuery.
    • Visualizing data using tools like Looker Studio (formerly Data Studio).
    • Basics of data cleaning and preparation.

  • Data Engineering Basics

     

    • Basic ETL (Extract, Transform, Load) workflows.
    • Familiarity with batch and stream processing pipelines.
    • Understanding how to move and transform data between GCP services.

  • Security and Governance

     

    • Understanding IAM (Identity and Access Management) roles and permissions for data.
    • Securing data using encryption and GCP’s built-in tools.
    • Managing data compliance and governance in GCP.

  • Collaboration and Integration

    • Integrating data workflows with other GCP tools.
    • Using APIs and SDKs to connect with external systems.
    • Collaboration with teams using shared GCP resources.

     

Who Should Attend the training ?

  • Aspiring Data Professionals: Individuals looking to kickstart their careers in the data field.
  • Professionals who want to enhance their data handling and analysis capabilities.
  • Fresh Graduates and Students: Those keen on building foundational skills in data processing and analysis.
  • IT Professionals: Tech experts aiming to expand their expertise in data-driven decision-making.
  • Career Switchers: Individuals from non-technical backgrounds seeking to transition into the world of data.

Prerequisites:

  • Candidates have a basic understanding of cloud computing concepts like infrastructure as a service (IaaS), platform as a service (PaaS), and software as a service (SaaS).

    • Why choose CloudThat as your training partner?

    • Specialized GCP Focus: CloudThat specializes in cloud technologies, offering focused and specialized training programs. We are Authorized Trainers for the Google Cloud Platform. This specialization ensures in-depth coverage of GCP services, use cases, best practices, and hands-on experience tailored specifically for GCP.
    • Industry-Recognized Trainers: CloudThat has a strong pool of industry-recognized trainers certified by GCP. These trainers bring real-world experience and practical insights into the training sessions, comprehensively understanding how GCP is applied in different industries and scenarios.
    • Hands-On Learning Approach: CloudThat emphasizes a hands-on learning approach. Learners can access practical labs, real-world projects, and case studies that simulate actual GCP environments. This approach allows learners to apply theoretical knowledge in practical scenarios, enhancing their understanding and skill set.
    • Customized Learning Paths: CloudThat understands that learners have different levels of expertise and varied learning objectives. We offer customized learning paths, catering to beginners, intermediate learners, and professionals seeking advanced GCP skills.
    • Interactive Learning Experience: CloudThat's training programs are designed to be interactive and engaging. We utilize various teaching methodologies like live sessions, group discussions, quizzes, and mentorship to keep learners engaged and motivated throughout the course.
    • Placement Assistance and Career Support: CloudThat often provides placement assistance and career support services. This includes resume building, interview preparation, and connecting learners with job opportunities through our network of industry partners and companies looking for GCP-certified professionals.
    • Continuous Learning and Updates: CloudThat ensures that our course content is regularly updated to reflect the latest trends, updates, and best practices within the GCP ecosystem. This commitment to keeping the content current enables learners to stay ahead in their GCP knowledge.
    • Positive Reviews and Testimonials: Reviews and testimonials from past learners can strongly indicate the quality of training provided. You can Check feedback and reviews about our GCP courses that can provide potential learners with insights into the effectiveness and value of the training.

    Course Outline:- Download Course Outline

    Topics

    • Data Engineering Tasks and Components
    • Data Replication and Migration
    • The Extract and Load Data Pipeline Pattern
    • The Extract, Load, and Transform Data Pipeline Pattern
    • The Extract, Transform, and Load Data Pipeline Pattern
    • Automation Techniques

    Objectives

    • Understand the role of a data engineer
    • Identify data engineering tasks and core components used on Google Cloud.
    • Understand how to create and deploy data pipelines of varying patterns on Google Cloud.
    • Identify and utilize various automation techniques on Google Cloud.

    Activities

    • 7 labs 1 Quiz

    Lab Topics

    • Introduction to SQL for BigQuery and Cloud SQL
    • BigQuery: Qwik Start - Console
    • BigQuery: Qwik Start - Command Line
    • Explore an Ecommerce Dataset with SQL in BigQuery
    • Derive Insights from BigQuery Data: Challenge Lab

    Objectives

    • Explore SQL keywords
    • you will learn how to use Cloud SQL to create and manage databases and tables.
    • you will get hands-on practice with additional SQL keywords that manipulate and edit data.

    Activities

    • Labs

    Lab Topics

    • Looker Data Explorer - Qwik Start
    • •Filtering and Sorting Data in Looker
    • Merging Results from Different Explores in Looker
    • Looker Functions and Operators
    • Prepare Data for Looker Dashboards and Reports: Challenge Lab

    Objectives

    • You will learn filtering, sorting, and pivoting data.
    • Merging results from different Looker Explores.
    • Using functions and operators to build Looker dashboards and reports for data analysis and visualization.

    Activities

    • 5 Labs

    Topics

    • AI Foundations
    • AI Development Option
    • AI Development Workflow
    • Generative AI

    Objectives

    • Explores the technologies, products, and tools available throughout the data-to-AI life cycle, encompassing AI foundations, development, and solutions.
    • To help data scientists, AI developers, and ML engineers enhance their skills and knowledge through engaging learning experiences and practical hands-on exercises.

    Activities

    • 4 labs

    Lab Topics

    • Cloud Storage: Qwik Start - Cloud Console
    • Cloud Storage: Qwik Start - CLI/SDK
    • Cloud IAM: Qwik Start
    • Cloud Monitoring: Qwik Start
    • Cloud Run Functions: Qwik Start - Console
    • Cloud Run Functions: Qwik Start - Command Line
    • Pub/Sub: Qwik Start - Console
    • Pub/Sub: Qwik Start - Command Line
    • Pub/Sub: Qwik Start - Python

    Objectives

    • These labs will help you to get practical experience through labs that dive into Cloud Storage and other key application services like Monitoring and Cloud Functions.

    Activities

    • 9 Labs

    Lab Topics

    • Optimizing Cost with Google Cloud Storage

    Objectives

    • This lab will help you to use Cloud Run functions and Cloud Scheduler to identify and clean up wasted cloud resources.

    Activities

    • 1 Lab

    Lab Topics

    • Cloud IAM: Qwik Start
    • IAM Custom Roles
    • Service Accounts and Roles: Fundamentals
    • VPC Network Peering
    • User Authentication: Identity-Aware Proxy
    • Getting Started with Cloud KMS
    • Setting up a Private Kubernetes Cluster
    • Implement Cloud Security Fundamentals on Google Cloud: Challenge Lab

    Objectives

    • It will help you for creating and assigning roles with Identity and Access Management (IAM)
    • Creating and managing service accounts.
    • Enabling private connectivity across virtual private cloud (VPC) networks.
    • Restricting application access using Identity-Aware Proxy.
    • Managing keys and encrypted data using Cloud Key Management Service (KMS).
    • Creating a private Kubernetes cluster.

    Activities

    • 8 Labs

    Certification

    • CloudThat Course Completion Certificate

    Click to Zoom

    Select Course date

    Loading Dates...
    Add to Wishlist

    Course ID: 23723

    Course Price at

    Loading price info...
    Enroll Now

    This role focuses on learning foundational data skills, understanding key Google Cloud services, and working with data storage, processing, and analysis tools. It's ideal for those starting their career in data or transitioning into the field.

    Basic understanding of data concepts (structured/unstructured data). Familiarity with SQL for querying databases. Awareness of Google Cloud services like BigQuery, Cloud Storage, and Dataflow.

    Beginners in data analytics, engineering, or data science. IT professionals looking to gain foundational knowledge in GCP. Students and early-career professionals interested in cloud data technologies.

    Learn to store, manage, and query data using GCP tools. Understand the basics of data analysis and visualization. Explore data pipelines, ETL workflows, and streaming data. Gain an overview of security and compliance for data in GCP.

    Start with Google’s introductory cloud courses. Focus on data services such as BigQuery and Cloud Storage. Gain hands-on experience with GCP’s free tier or labs.

    Advance to Professional Data Engineer certification. Gain expertise in machine learning or advanced analytics in GCP. Transition into roles like Data Analyst, Data Engineer, or Cloud Engineer.

    Enquire Now