Application Programming Interfaces (APIs) are a great tool for collecting data.
They have already been widely adapted in places like travel websites, which use APIs to pull information from hotel and airline sites. However, sometimes APIs can’t deliver the data needed all at once, and need to be called hundreds, thousands, or millions of times to provide the full dataset. In this case, manually calling the API is inefficient and time-consuming. Even establishing an automated process to serially call the API requires a lot of time and effort.
In this 30-minute recorded webinar Thorogood Data and Analytics consultants Melissa Horan and Lauren Potechin discuss the different methods of parallelizing API calls, and their benefits, limitations and applications.
Methods of API Parallelization (25 mins)
What we cover:
- What are APIs?
- The limitations of APIs
- The methods of calling APIs in parallel
Is it for you?
- Are you interested in collecting data using APIs?
- Do you need to make multiple API calls efficiently?
- Are you looking for the best method for parallel processing?