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'd like to dive deeper into data strategy and infrastructure and you'd like to support me, you can consider becoming a paid member of my Substack. I have over 100 articles that cover everything from data engineering 101 to leading data teams. Sign up with the link below and get 30% off. - https://seattledataguy.substack.com/1... If you'd like to read up on my updates about the data field, then you can sign up for our newsletter here. https://seattledataguy.substack.com/​​ Or check out my blog https://www.theseattledataguy.com/ And if you want to support the channel, then you can become a paid member of my newsletter https://seattledataguy.substack.com/s... Tags: Data engineering projects, Data engineer project ideas, data project sources, data analytics project sources, data project portfolio _____________________________________________________________ Subscribe:    / @seattledataguy   _____________________________________________________________ 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.