Extract, Transform, and Load Data

This course is part of CertNexus Certified Data Science Practitioner Professional Certificate

Instructors: Stacey McBrine

Access provided by American University of Bahrain

5,474 already enrolled

4 modules

Gain insight into a topic and learn the fundamentals.

37 reviews

Intermediate level

Recommended experience

2 weeks to complete

at 10 hours a week

Flexible schedule

Learn at your own pace

4 modules

Gain insight into a topic and learn the fundamentals.

37 reviews

Intermediate level

Recommended experience

2 weeks to complete

at 10 hours a week

Flexible schedule

Learn at your own pace

Skills you'll gain

Details to know

Shareable certificate

Add to your LinkedIn profile

Assessments

3 assignments¹

AI Graded see disclaimer

Taught in English

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Build your Data Analysis expertise

This course is part of the CertNexus Certified Data Science Practitioner 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 CertNexus

There are 4 modules in this course

This course is designed for business and data professional seeking to learn the first technical phase of the data science process known as Extract, Transform and Load or ETL.

Learners will be taught how to collect data from multiple sources so it is available to be transformed and cleaned and then will dive into collected data sets to prepare and clean data so that it can later be loaded into its ultimate destination. In the conclusion of the course learners will load data into its ultimate destination so that it can be analyzed and modeled. The typical student in this course will have experience working with data and aptitude with computer programming.

The first truly hands-on technical phase of the data science process is actually a combination of related tasks known as extract, transform, and load (ETL). This is where you, the data science practitioner, start to mold and shape the data so that it can be as useful as possible for the later steps in the data science process. In this course, you'll go through each ETL task in order, starting with "E" (extract).

What's included

12 videos7 readings1 assignment1 discussion prompt3 ungraded labs

12 videos Total 66 minutes

Course Intro: Extract, Transform, and Load Data 3 minutes
Structure of Data 7 minutes
Terms Describing Portions of Data 3 minutes
Big Data 5 minutes
Data Sources 6 minutes
Public APIs and Web Scraping 7 minutes
Data Read from Cloud Storage 4 minutes
Extract, Transform, and Load (ETL) 8 minutes
CSV Files 4 minutes
SQL Queries 7 minutes
NoSQL Queries 6 minutes
Data Consolidation and Joins 6 minutes

7 readings Total 60 minutes

Overview 2 minutes
Get help and meet other learners. Join your Community! 5 minutes
Open Datasets 20 minutes
Guidelines for Reading Data from CSV Files 3 minutes
Guidelines for Extracting Data with Database Queries 10 minutes
Inner Join Example 15 minutes
Guidelines for Consolidating Data from Multiple Sources 5 minutes

1 assignment Total 30 minutes

Extracting Data 30 minutes

1 discussion prompt Total 5 minutes

Reflect on What You've Learned 5 minutes

3 ungraded labs Total 95 minutes

Reading Data from CSV Files 20 minutes
Extracting Data with Database Queries 45 minutes
Consolidating Data from Multiple Sources 30 minutes

The next step in the ETL process is transformation. You'll spend this next module adjusting your data so that it's in a more useful state.

What's included

9 videos7 readings1 assignment1 discussion prompt4 ungraded labs

9 videos Total 55 minutes

Data Preparation and Cleaning 7 minutes
Types of Data and Data Operations 7 minutes
Continuous vs. Discrete Variables 5 minutes
Data Parsing 2 minutes
Data Irregularities 9 minutes
Correction of Data Formats and Date Conversion 9 minutes
Deduplication 4 minutes
Word Embedding 8 minutes
Image Data Representation 4 minutes

7 readings Total 60 minutes

Overview 2 minutes
Guidelines for Parsing Data 3 minutes
Guidelines for Handling Irregular and Unusable Data 10 minutes
Guidelines for Correcting Data Formats 15 minutes
Guidelines for Deduplicating Data 5 minutes
Text Data Transformation Techniques 15 minutes
Guidelines for Transforming Data 10 minutes

1 assignment Total 30 minutes

Transforming Data 30 minutes

1 discussion prompt Total 5 minutes

Reflect on What You've Learned 5 minutes

4 ungraded labs Total 145 minutes

Handling Irregular and Unusable Data 20 minutes
Correcting Data Formats 30 minutes
Deduplicating Data 20 minutes
Handling Textual Data 75 minutes

The last step in the ETL process is loading. In this module, you'll take the data you transformed and put it into a destination format and location, where it will be ready for you to work on as the project progresses.