Prepare Data for Exploration

Module 1: Data Types and Structures

Introduction to data exploration

00:00
Hallie: Fascinating data insights

00:00
Data collection in our world

00:00
Determine what data to collect

00:00
Discover data formats

00:00
Continue exploring structured data

00:00
Know the type of data you’re working with

00:00
Data table components

00:00
Meet wide and long data

00:00

9 readings

Course 3 overview: Set your expectations

00:00
Select the right data

00:00
Data formats in practice

00:00
The effects of different structures

00:00
Data modeling levels and techniques

00:00
Use Boolean logic

00:00
Step-by-Step: Meet wide and long data

00:00
Transforming data

00:00
Glossary terms from module 1

00:00

6 quizzes

1 discussion prompt

2 plugins

Module 2: Data responsibility

Introduction to bias, credibility, privacy, and ethics

00:00
Bias: From questions to conclusions

00:00
Biased and unbiased data

00:00
Understand bias in data

00:00
Identify good data sources

00:00
What is “bad” data?

00:00
Essential data ethics

00:00
Optional refresher: Alex and the importance of data ethics

00:00
Prioritize data privacy

00:00
Andrew: The ethical use of data

00:00
Features of open data

00:00
Andrew: Steps for ethical data use

00:00

4 readings

6 quizzes

1 discussion prompt

Module 3: Database essentials

All about databases

00:00
Database features and components

00:00
Demystify metadata

00:00
Manage data with metadata

00:00
Megan: Fun with metadata

00:00
So many places to find data

00:00
Import data from spreadsheets and databases

00:00
Sort and filter to focus on relevant data

00:00
Get to know BigQuery, including sandbox and billing options

00:00
BigQuery in action

00:00

12 readings

Maximize databases in data analytics

00:00
Inspect a dataset: A guided, hands-on tour

00:00
Metadata is as important as the data itself

00:00
Metadata and metadata repositories

00:00
Step-by-Step: Import data from spreadsheets and databases

00:00
Import data dynamically

00:00
Explore public datasets

00:00
Set up your BigQuery account

00:00
Get started with BigQuery

00:00
Step-by-Step: BigQuery in action

00:00
In-depth guide: SQL best practices

00:00
Glossary terms from module 3

00:00

12 quizzes

Module 3 challenge

00:00
Test your knowledge on working with databases

00:00
Test your knowledge on metadata

00:00
Test your knowledge on accessing data sources

00:00
Hands-On Activity: Clean data in spreadsheets with sorting and filtering

00:00
Self-Reflection: Compare databases and spreadsheets

00:00
Test your knowledge on sorting and filtering

00:00
Hands-On Activity: Introduction to BigQuery

00:00
Hands-On Activity: Create a custom table in BigQuery

00:00
Hands-On Activity: Choose the right tool for the job

00:00
Hands-On Activity: More practice with SQL

00:00
Test your knowledge on using SQL with large datasets

00:00

Course Content

Module 1: Data Types and Structures

Introduction to data exploration

Hallie: Fascinating data insights

Data collection in our world

Determine what data to collect

Discover data formats

Continue exploring structured data

Know the type of data you’re working with

Data table components

Meet wide and long data

9 readings

Course 3 overview: Set your expectations

Select the right data

Data formats in practice

The effects of different structures

Data modeling levels and techniques

Use Boolean logic

Step-by-Step: Meet wide and long data

Transforming data

Glossary terms from module 1

6 quizzes

Module 1 challenge

Test your knowledge on collecting data

Optional Self-Reflection: Unstructured data

Test your knowledge on data formats and structures

Hands-On Activity: Introduction to Kaggle

Test your knowledge on data types, fields, and values

1 discussion prompt

Meet and greet

2 plugins

Refresher: Your Google Data Analytics Certificate roadmap

Differentiate data types

Module 2: Data responsibility

Introduction to bias, credibility, privacy, and ethics

Bias: From questions to conclusions

Biased and unbiased data

Understand bias in data

Identify good data sources

What is “bad” data?

Essential data ethics

Optional refresher: Alex and the importance of data ethics

Prioritize data privacy

Andrew: The ethical use of data

Features of open data

Andrew: Steps for ethical data use

4 readings

Data anonymization

The open data debate

Resources for open data

Glossary terms from module 2

6 quizzes

Module 2 challenge

Test your knowledge on unbiased and objective data

Test your knowledge on data credibility

Test your knowledge on data ethics and privacy

Hands-On Activity: Kaggle datasets

Test your knowledge on open data

1 discussion prompt

Account for bias

Module 3: Database essentials

All about databases

Database features and components

Demystify metadata

Manage data with metadata

Megan: Fun with metadata

So many places to find data

Import data from spreadsheets and databases

Sort and filter to focus on relevant data

Get to know BigQuery, including sandbox and billing options

BigQuery in action

12 readings

Maximize databases in data analytics

Inspect a dataset: A guided, hands-on tour

Metadata is as important as the data itself

Metadata and metadata repositories

Step-by-Step: Import data from spreadsheets and databases

Import data dynamically

Explore public datasets

Set up your BigQuery account