Data Transformation in the Cloud

This course is part of Google Cloud Data Analytics Professional Certificate

Instructor: Google Cloud Training

Access provided by EDGE Group

3,298 already enrolled

3 modules

Gain insight into a topic and learn the fundamentals.

28 reviews

Beginner level

No prior experience required

2 weeks to complete

at 10 hours a week

Flexible schedule

Learn at your own pace

3 modules

Gain insight into a topic and learn the fundamentals.

28 reviews

Beginner level

No prior experience required

2 weeks to complete

at 10 hours a week

Flexible schedule

Learn at your own pace

What you'll learn

Describe the steps of the data journey and how they are used to drive data-driven decision making.
Recognize the role of data transformation in preparing data for analysis.
Describe the benefits and challenges of transforming data in the cloud.
Identify the key components of a data transformation plan.

Skills you'll gain

Tools you'll learn

Cloud Storage

Details to know

Shareable certificate

Add to your LinkedIn profile

Assessments

13 assignments

Taught in English

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This course is part of the Google Cloud Data Analytics Professional Certificate

When you enroll in this course, you'll also be enrolled in this Professional Certificate.

Learn new concepts from industry experts
Gain a foundational understanding of a subject or tool
Develop job-relevant skills with hands-on projects
Earn a shareable career certificate from Google Cloud

There are 3 modules in this course

Hi learner! This is the third course of the Google Cloud Data Analytics Certificate. Tap into your creativity as you explore the world of advanced principles of data visualization. You'll discover the benefits and challenges of transforming data in the cloud and the common tools and methods used to collect, process, and store data.

Embark on the ultimate data adventure! This module maps out the cloud data journey, revealing the secrets of collecting and preparing data to fuel those brilliant business insights. You’ll uncover the power of structure, the pros and cons of cloud transformation, and the essential tools that shape data along the way.

What's included

8 videos11 readings3 assignments1 app item1 plugin

8 videos Total 14 minutes

Introduction to course 3 2 minutes
Alyx: Data analysts help others learn from data 1 minute
Welcome to module 1 1 minute
Stages of the data journey 3 minutes
Steps for effective data collection 2 minutes
The process stage ensures clean and consistent data 2 minutes
Manual and automated transformation 3 minutes
Wrap-up 1 minute

11 readings Total 180 minutes

Course 3 overview 20 minutes
Helpful resources and tips 10 minutes
Lab technical tips 10 minutes
Explore your Course 3 scenario: TheLook eCommerce 10 minutes
The data journey is a flexible path 20 minutes
Impacts of the data journey on decision making 20 minutes
[Supplemental] Process and summarize data 20 minutes
Techniques used to transform data, part 1 20 minutes
Techniques used to transform data, part 2 20 minutes
Storage options for transformed data 20 minutes
Glossary terms from module 1 10 minutes

3 assignments Total 66 minutes

Module 1 challenge 50 minutes
Test your knowledge: Introduction to the data journey and collecting data 8 minutes
Test your knowledge: The processing and storage stages of the data journey 8 minutes

1 app item Total 90 minutes

Practice Transformation Methods 90 minutes

1 plugin Total 15 minutes

Accessing and completing labs 15 minutes

Become the architect of data flow! Discover how a data pipeline works, guiding data from its origins all the way to analysis. You'll dive into each stage of the process and even get the chance to build your own SQL pipeline. Hands-on experience for the win!

What's included

11 videos9 readings5 assignments1 app item

11 videos Total 32 minutes

Welcome to module 2 1 minute
Data pipelines in the cloud 3 minutes
Alyssa: Improve systems by collecting data and asking questions 3 minutes
The difference between ELT and ETL 4 minutes
Data ingestion methods that suit your needs 4 minutes
Data mapping helps ensure consistent data 4 minutes
Introduction to profiling and cleaning data 3 minutes
Common ways to manipulate data 3 minutes
Different approaches to loading data 3 minutes
Overview of data validation strategies and rules 4 minutes
Wrap-up 1 minute

9 readings Total 170 minutes

Overview of data pipeline stages and benefits 20 minutes
Strategies and tools for efficient data ingestion 20 minutes
Data transformation steps to ensure reliable data 20 minutes
Data transformation techniques that achieve different business needs 20 minutes
Transformation approaches for securing data 20 minutes
Data anonymization with generative models 20 minutes
Data dictionaries and monitoring help maintain data integrity 20 minutes
Analysis and visualization after the data pipeline 20 minutes
Glossary terms from module 2 10 minutes

5 assignments Total 88 minutes

Module 2 challenge 50 minutes
Test your knowledge: Introduction to data pipelines 10 minutes
Test your knowledge: The extract stage of data pipelines 10 minutes
Test your knowledge: The transformation stage of data pipelines 10 minutes
Test your knowledge: The load stage of data pipelines 8 minutes

1 app item Total 90 minutes

Creating and managing SQL pipelines 90 minutes

Ready to streamline your data operations? This module is your guide to tackling the massive amounts of data that modern businesses generate. You'll explore strategies to optimize data for analysis, and you'll practice cleaning, summarizing, and joining data sets – skills that make your insights shine.