Google Cloud Associate Data Practitioner Exam Cram

Google Cloud Associate Data Practitioner Exam Cram
Published 3/2025
MP4 | Video: h264, 1920×1080 | Audio: AAC, 44.1 KHz

Unlock Your Data Career Potential: Master the Google Cloud Associate Data Practitioner Certification

What you’ll learn

Master the Exam Objectives: Demystify the GCP Professional Data Engineer certification exam and understand its core components.

Implement Data Engineering Best Practices: Apply proven strategies for designing and building efficient, reliable data pipelines on GCP.

rchestrate Data Ingestion & Storage: Seamlessly extract and load data into diverse GCP storage solutions, including Cloud Storage and Bigtable.

Navigate GCP’s Data Storage Ecosystem: Choose the right storage services for structured (Cloud SQL, Spanner, BigQuery), unstructured (Cloud Storage, Filestore),

Fortify Your Data Security & Compliance: Implement robust security measures and ensure adherence to stringent data privacy regulations.

Leverage Powerful Data Management Tools: Master DataPrep and Data Catalog for effective data governance.

Visualize Data Insights: Transform raw data into compelling visualizations using Data Studio.

ngineer High Availability & Disaster Recovery: Design resilient data solutions for Cloud Storage and Cloud SQL.

Harness the Power of AI/ML: Explore BigQuery ML and AutoML for advanced data analysis.

Requirements

olid understanding of fundamental data management, engineering, and privacy concepts.

At least six months of practical experience with GCP services (networking, security, storage).

Hands-on experience with SQL databases and relational database concepts

Description

Overview

Section 1: Introduction

Lecture 1 Course Trailer

Lecture 2 Course Introduction

Lecture 3 What is the GCP Associate Data Practitioner Certification?

Lecture 4 Associate Data Practitioner Certification Exam Objectives

Lecture 5 Certification Exam Process

Lecture 6 Downloadable Course Resources

Section 2: Data Preparation and Ingestion

Lecture 7 Discussion – Importance of Data Practitioners

Lecture 8 Data Quality Fundamentals

Lecture 9 Data Transfer Tools (Storage Transfer Service and Transfer Appliance)

Lecture 10 Data Cleansing and Profiling

Lecture 11 Data Transfer Formats

Lecture 12 Data Structures, Files and Types

Lecture 13 Whiteboard – Mapping business requirements to Use Cases

Lecture 14 Demonstration – BigQuery

Lecture 15 Module Two Review

Section 3: Data Pipeline Orchestration (65 minutes)

Lecture 16 Selecting a data transformation tool in Google Cloud

Lecture 17 Evaluate use cases for ETL/ELT

Lecture 18 Choose products required to implement transformation pipelines

Lecture 19 Demonstration: Monitor Dataflow pipeline progress using the Dataflow job UI

Lecture 20 Demonstration: Review and analyze logs in Cloud Logging and Cloud Monitoring

Lecture 21 Whiteboard Discussion: Select a data orchestration solution

Lecture 22 Whiteboard Discussion- Identify use cases for event-driven data ingestion

Lecture 23 Demonstration – Use Eventarc triggers in event-driven pipelines

Lecture 24 Module Review

Lecture 25 Resources

Lecture 26 Course Closeout

Anyone who is looking to pass this exam,Data professionals such as data analysts, data practitioners, data engineers,IT professionals wishing to level up their data skills