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Stacey McBrine, Sarah Haq, and Megan Smith Branch

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.

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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.

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What's inside

Syllabus

Extract Data
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).
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Transform Data
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.
Load Data
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.
Apply What You've Learned
You'll work on a project in which you'll apply your knowledge of the material in this course to a practical scenario.

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Presents an industry-standard approach to data science, referred to as Extract, Transform, Load (ETL)
Core instructors have established experience and recognition in data science
Appropriate for individuals with prior data experience and programming knowledge
Course is not appropriate for absolute beginners in data science or programming

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Reviews summary

Beginner-friendly etl course

Learners say this introductory course on ETL (Extract, Transform, and Load) data is a great starting point for those new to the field. The course is described as beginner-friendly and less advanced learners claim it is easy to understand. Reviewers also appreciate the informative material and say they have learned a lot about basic ETL concepts.
Covers fundamental ETL concepts.
"informative"
"The course provides knowledge from basic about ETL and its db"
"Excellent"
Suitable for novices.
"In the course description it is indicated that an middle level of knowledge is requied to complete the course (supposedly python, numpy, pandas, sql etc skills are needed). Actually, the couse covers only very basic concepts, and the tasks are to rewrite the code from the reference book. The course is too easy and it gives little knowledge."
"Easy to understand material"
"The course provides knowledge from basic about ETL and its db"

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Extract, Transform, and Load Data with these activities:
Data Integration Fundamentals by Paulraj Ponniah
Gain a comprehensive understanding of ETL principles
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  • Read chapters on data extraction, transformation, and loading
  • Review case studies and examples of ETL implementation
ETL Practice Problems
Start the course with a strong foundation by practicing ETL concepts
Browse courses on ETL
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  • Solve practice problems on data extraction techniques
  • Work through examples of data transformation methods
  • Practice loading data into various target systems
Interactive ETL Tutorials
Enhance understanding of ETL concepts through engaging tutorials
Browse courses on ETL
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  • Follow interactive tutorials on data extraction techniques
  • Complete exercises on data transformation methods
  • Practice loading data into various target systems
Four other activities
Expand to see all activities and additional details
Show all seven activities
ETL Coding Exercises
Develop proficiency in ETL by completing coding exercises
Browse courses on ETL
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  • Code data extraction scripts in your preferred programming language
  • Write code to transform data and handle data quality issues
  • Develop code to load data into target databases or data warehouses
ETL Concept Map
Solidify understanding of ETL by creating a visual representation
Browse courses on ETL
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  • Create a concept map that visually represents ETL processes
  • Include key concepts, techniques, and challenges in ETL
ETL Knowledge Sharing
Reinforce knowledge by sharing it with others
Browse courses on ETL
Show steps
  • Identify opportunities to mentor colleagues or peers
  • Share your knowledge and experience in ETL
  • Provide guidance and support to those seeking to learn ETL
Data ETL Challenge
Test your skills and knowledge in a practical setting
Browse courses on ETL
Show steps
  • Participate in ETL challenges or hackathons
  • Work on real-world ETL scenarios
  • Collaborate with others to solve complex ETL problems

Career center

Learners who complete Extract, Transform, and Load Data will develop knowledge and skills that may be useful to these careers:
Data Integration Architect
A Data Integration Architect designs and implements data integration solutions to combine data from multiple sources. This course may be useful for those seeking to enter this field by providing a foundation in data extraction, transformation, and loading, which are essential skills for building and maintaining data integration pipelines.
Data Quality Analyst
A Data Quality Analyst ensures that data is accurate, complete, and consistent. This course may be useful for those seeking to enter this field by providing a foundation in data extraction, transformation, and loading, which are essential skills for identifying and correcting data errors.
Data Steward
A Data Steward is responsible for the quality and integrity of data. This course may be useful for those seeking to enter this field by providing a foundation in data extraction, transformation, and loading, which are essential skills for understanding how data is collected, used, and shared.
Data Analyst
A Data Analyst collects, analyzes, and interprets data to identify trends and patterns that support decision-making. This course may be useful for those seeking to enter this field by providing a foundation in data extraction, transformation, and loading, which are essential skills for preparing data for analysis.
Data Scientist
A Data Scientist builds and deploys machine learning models to make predictions and solve business problems. This course may be useful for those seeking to enter this field by providing a foundation in data extraction, transformation, and loading, which are essential skills for preparing data for modeling.
Data Warehouse Manager
A Data Warehouse Manager oversees the design, implementation, and maintenance of data warehouses. This course may be useful for those seeking to enter this field by providing a foundation in data extraction, transformation, and loading, which are essential skills for managing and storing large volumes of data.
Data Catalog Manager
A Data Catalog Manager manages and maintains a data catalog, which is a repository of information about data assets. This course may be useful for those seeking to enter this field by providing a foundation in data extraction, transformation, and loading, which are essential skills for organizing and documenting data.
Database Administrator
A Database Administrator manages and maintains databases to ensure data integrity and availability. This course may be useful for those seeking to enter this field by providing a foundation in data extraction, transformation, and loading, which are essential skills for managing data storage and retrieval.
Data Engineer
A Data Engineer designs and implements data architectures and pipelines to support data-driven decision-making. This course may be useful for those seeking to enter this field by providing a foundation in data extraction, transformation, and loading, which are essential skills for managing data infrastructure and ensuring data quality.
Business Intelligence Analyst
A Business Intelligence Analyst uses data to identify opportunities and solve problems within an organization. This course may be useful for those seeking to enter this field by providing a foundation in data extraction, transformation, and loading, which are essential skills for gathering and preparing data for analysis.
Information Architect
An Information Architect designs and organizes information systems to ensure that users can easily find and use the information they need. This course may be useful for those seeking to enter this field by providing a foundation in data extraction, transformation, and loading, which are essential skills for managing and structuring data.
Data Governance Analyst
A Data Governance Analyst develops and implements data governance policies and procedures to ensure that data is used ethically and responsibly. This course may be useful for those seeking to enter this field by providing a foundation in data extraction, transformation, and loading, which are essential skills for understanding how data is collected, used, and shared.
Data Librarian
A Data Librarian manages and preserves data to ensure that it is accessible and usable. This course may be useful for those seeking to enter this field by providing a foundation in data extraction, transformation, and loading, which are essential skills for organizing and storing data.
Software Engineer
A Software Engineer designs, develops, and maintains software applications. This course may be useful for those seeking to enter this field by providing a foundation in data extraction, transformation, and loading, which are essential skills for building data-driven applications.
Data Protection Officer
A Data Protection Officer ensures that an organization complies with data protection laws and regulations. This course may be useful for those seeking to enter this field by providing a foundation in data extraction, transformation, and loading, which are essential skills for understanding how data is collected, used, and shared.

Reading list

We've selected 12 books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Extract, Transform, and Load Data.
Nathan Yau's book practical guide to data preparation, which is the first step in the ETL process. It covers everything from data cleaning to data transformation, and it's a great resource for anyone who wants to learn more about this essential topic. It can be used as a reference tool or as additional reading.
Wes McKinney's book comprehensive guide to using Python for data analysis. It covers everything from data cleaning to data visualization, and it's a great resource for anyone who wants to learn how to use Python for data science. It can be used as a textbook or as a reference tool.
Hadley Wickham's and Garrett Grolemund's book comprehensive guide to using R for data science. It covers everything from data cleaning to data visualization, and it's a great resource for anyone who wants to learn how to use R for data science. It can be used as a textbook or as a reference tool.
Provides a comprehensive overview of deep learning. It covers everything from the basics of deep learning to the latest advances in the field.
Provides a comprehensive overview of reinforcement learning. It covers everything from the basics of reinforcement learning to the latest advances in the field.
Provides a step-by-step guide to storytelling with data. It covers everything from finding the right story to telling it in a way that is both engaging and persuasive.
Wes McKinney's book hands-on guide to data wrangling with Python. It covers all the basics of data cleaning and transformation, and it's a great resource for anyone who wants to learn how to use Python for data science. It can be used as a reference tool or as additional reading.
John Paul Mueller's and Luca Massaron's book comprehensive introduction to data science. It covers everything from data collection to data analysis, and it's a great resource for anyone who wants to learn more about this field. It can be used as a reference tool or as additional reading.
Provides a comprehensive overview of the ethical issues surrounding data science. It covers everything from data privacy to algorithmic bias.
By John Paul Mueller and Luca Massaron gentle introduction to machine learning. It covers all the basics of machine learning, and it's a great resource for anyone who wants to learn more about this topic without getting too deep into the math. It can be used as a reference tool or as additional reading.

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