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:

Disclosure - I have a financial stake in both

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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.

*I do participate in affiliate programs, if a link has an "*" by it, then I may receive a small portion of the proceeds at no extra cost to you.

[nicky_rads]

Solid overview. Working with APIs is a good skill set to have for data engineering. Turning JSON formatted data into tabular data for humans to understand is very important!

[lafcadiothelion]

Enjoying these back to the basics videos! Perfect timing for me too

[SegueGreene]

Love this, perfect level of detail for where i'm at <3

[marshallyale]

You briefly discussed it, but could you talk a little bit more about the config file you discuss for parsing? I just know my code starts to become a little verbose when I have 30 different functions to parse different API calls, especially if there's additional checks that an http status code can't tell you

[rickr]

can you make a video about how to deal with schemas of APIs and how they change over time :) dates and temporal data in particular

[artyomashigov]

Thanks for the video. The quality though is 720p.

[bwb]

yea but its really bored man
everyone knows that so superficial
when making this with chatgpt at least think like how can i be useful to people rather doing spam like videos, at least add paginated calls, airflow http operators, things like that man. i am really bored .