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Building a Retail Data Pipeline

IntermediateSkill Level
4.7+
887 reviews
Updated 09/2024
Test your Data engineering skills by creating a data pipeline to analyze E-commerce business of Walmart!
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Included withPremium or Teams

PythonData ManipulationData Engineering
45 min
1 Task
1,500 XP
12,144

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Project Description

Building a Retail Data Pipeline

Mastering data pipelines is essential for Data Engineers today. It involves extracting, transforming, and loading data — a fundamental task that ensures information flows smoothly.In this project, you will work with retail data from a multinational retail corporation Walmart. You will retrieve data from different sources, like SQL and parquet; prepare the data using some transformation techniques, and finally load the data in an easy-to-access format.

Building a Retail Data Pipeline

Test your Data engineering skills by creating a data pipeline to analyze E-commerce business of Walmart!
Start Project
  • 1

    Apply your Data Engineering skills to extract, transform, and load data for future analysis!

Don’t just take our word for it

*4.7
from 887 reviews
80%
19%
1%
0%
0%
  • Asim
    2 days ago

    It was great

  • Augusto
    2 days ago

  • Lance
    3 days ago

  • andrea
    3 days ago

  • Darren
    5 days ago

    When I submitted the project it failed because it wanted the sales column to be Avg_Sales instead of Weekly_Sales, but that is never mentioned in the documentation.

  • Ruslan
    6 days ago

"It was great"

Asim

Augusto

Lance

FAQs

Is this project suitable for beginners?

Yes, this project is suitable for beginners.

What is the programming language of this project?

The programming language of this project is Python.

Can I add this project to my Data Portfolio?

Yes, you can add this project to your Data Portfolio once you have completed it.

Do I need to download any software to complete this project?

No, you can complete the project using DataCamp Workspace without needing to download any additional software.

    Join over 19 million learners and start Building a Retail Data Pipeline today!

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