Extracting Data From APIs As Data Engineers - The Basics And Challenges You'll Run Into

If you've had to build any data pipelines for analytics, then you're likely very familiar with the extract phase of an ELT or ETL.

As the name suggests the extract phase is when you connect to a data source and "extract" data from it. The most common data sources you'll be interacting with being databases, APIs, and file servers(via FTP or SFTP).

With my recent focus on going back to the basics, it occurred to me that I have never written about APIs and how we interact with them as data engineers.

Now, there are plenty of APIs that have caused me a lot of heartburn in my career and there are others that have been a piece of cake to handle.

But it all comes down to how the API is set up and the design choices made when it was built.

If you're looking for an out of the box solution to handle your API data extraction. You can check out the two below:

Portable For APIs - https://portable.io/

Estuary For Real Time Data Extraction - https://bit.ly/4eQC3oQ

Disclosure - I have a financial stake in both

Also, if you're looking to learn more about data engineering, then today October 4th 2024 there is a free conference going on that you should sign up.
https://www.accelevents.com/e/data-en...


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Tags: Data engineering projects, Data engineer project ideas, data project sources, data analytics project sources, data project portfolio

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About me:
I have spent my career focused on all forms of data. I have focused on developing algorithms to detect fraud, reduce patient readmission and redesign insurance provider policy to help reduce the overall cost of healthcare. I have also helped develop analytics for marketing and IT operations in order to optimize limited resources such as employees and budget. I privately consult on data science and engineering problems both solo as well as with a company called Acheron Analytics. I have experience both working hands-on with technical problems as well as helping leadership teams develop strategies to maximize their data.

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