Extract, Transform, and Load Data

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

Instructors: Stacey McBrine

Access provided by INEFOP - Instituto Nacional de Empleo y Formación Profesional de Uruguay

5,507 already enrolled

4 modules

Gain insight into a topic and learn the fundamentals.

39 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.

39 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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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 videosTotal 66 minutes

Course Intro: Extract, Transform, and Load Data3 minutes
Structure of Data7 minutes
Terms Describing Portions of Data3 minutes
Big Data5 minutes
Data Sources6 minutes
Public APIs and Web Scraping7 minutes
Data Read from Cloud Storage4 minutes
Extract, Transform, and Load (ETL)8 minutes
CSV Files4 minutes
SQL Queries7 minutes
NoSQL Queries6 minutes
Data Consolidation and Joins6 minutes

7 readingsTotal 60 minutes

Overview2 minutes
Get help and meet other learners. Join your Community!5 minutes
Open Datasets20 minutes
Guidelines for Reading Data from CSV Files3 minutes
Guidelines for Extracting Data with Database Queries10 minutes
Inner Join Example15 minutes
Guidelines for Consolidating Data from Multiple Sources5 minutes

1 assignmentTotal 30 minutes

Extracting Data30 minutes

1 discussion promptTotal 5 minutes

Reflect on What You've Learned5 minutes

3 ungraded labsTotal 95 minutes

Reading Data from CSV Files20 minutes
Extracting Data with Database Queries45 minutes
Consolidating Data from Multiple Sources30 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 videosTotal 55 minutes

Data Preparation and Cleaning7 minutes
Types of Data and Data Operations7 minutes
Continuous vs. Discrete Variables5 minutes
Data Parsing2 minutes
Data Irregularities9 minutes
Correction of Data Formats and Date Conversion9 minutes
Deduplication4 minutes
Word Embedding8 minutes
Image Data Representation4 minutes

7 readingsTotal 60 minutes

Overview2 minutes
Guidelines for Parsing Data3 minutes
Guidelines for Handling Irregular and Unusable Data10 minutes
Guidelines for Correcting Data Formats15 minutes
Guidelines for Deduplicating Data5 minutes
Text Data Transformation Techniques15 minutes
Guidelines for Transforming Data10 minutes

1 assignmentTotal 30 minutes

Transforming Data30 minutes

1 discussion promptTotal 5 minutes

Reflect on What You've Learned5 minutes

4 ungraded labsTotal 145 minutes

Handling Irregular and Unusable Data20 minutes
Correcting Data Formats30 minutes
Deduplicating Data20 minutes
Handling Textual Data75 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.