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Practice Data Engineering Skills with New Hands-On Projects

Find out how you can practice your Data Engineering skills with DataCamp's new hands-on projects.
Updated Aug 2023  · 3 min read

The modern data engineering tech stack is continuously growing along with the size and complexity of organizational datasets.

With the rise of big data, companies are looking for professionals who can not only collect and process data, but also store and manage it efficiently in the cloud data warehouses. Specifically, Google BigQuery, Snowflake, and Amazon Redshift.

Although possessing Python and SQL knowledge is essential, a data engineer should also have hands-on experience with cloud data warehouse intricacies, such as SQL dialect, data types, scaling options, and more.

The modern data engineering stack

On top of the Data Engineer with Python career track, which already offers a comprehensive path to gaining foundational data engineering skills, we are happy to announce the new Exploring London’s Travel Network Project available to practice Snowflake, Google BigQuery, and Amazon Redshift skills.

Inside Exploring London’s Travel Network Project

Over 1.5 million daily journeys are made across the extensive Transport for London (TFL) network.

With such a high volume of commuters, tourists, and residents on the move each day—how do most Londoners get around?

In this introductory Exploring London’s Travel Network Project, you will write SQL queries to find the most popular transport methods, examine peak hours, and identify rare periods when the Underground (known as "the tube" to locals) was less busy. Plus, you can interact directly with the modern cloud data warehouses–choose between Snowflake, BigQuery, or Redshift or complete all three project variations.

DataCamp Projects

If you completed other DataCamp projects before, you should be familiar with DataCamp Workspace, our modern data science notebook in the cloud.

Workspace provides seamless integrations with the most popular SQL databases and cloud warehouses and saves you hours on configurations and setup. Furthermore, you can accelerate your learning with Workspace AI Assistant, which could suggest best practices for writing SQL code and help fix errors.

If you want to explore working with cloud warehouses beyond the project's scope, head over to DataCamp Workspace and practice your skills with preconfigured sample data integrations.

DataCamp Projects in Workspace

DataLab

Skip the installation process and experiment with data science code in your browser with DataLab, DataCamp's AI-powered notebook.

Get Started
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How to Get Started

If you are completely new to Data Engineering, we recommend enrolling on the Data Engineer with Python track first. This will provide you with foundational knowledge in database management, data engineering concepts, cloud computing, SQL, Python, and Git. Find out precise steps on how to become a Data Engineer in 2023 in our guide.

After completion, you will have all the prerequisites to test your skills in the new Exploring London’s Travel Network Project and add this achievement to your data portfolio.

Conclusion

Practicing data engineering skills through hands-on projects is crucial for professionals looking to keep up with the ever-growing data engineering tech stack and complexity of organizational datasets. The Exploring London’s Travel Network Project offers a great opportunity to gain first experience with cloud data warehouses such as Snowflake, Google BigQuery, and Amazon Redshift.

Practice Data Engineering Skills with DataCamp

Try our introductory project 'Exploring London's Travel Network' and practice your Snowflake, Google BigQuery, and Amazon Redshift skills.

Start your Journey to Become a Data Engineer

Data Engineer

AdvancedSkill Level
57hrs
Gain in-demand skills to efficiently ingest, clean, manage data, and schedule and monitor pipelines, setting you apart in the data engineering field.
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