Please log in to watch this conference skillscast.
After exposing a background of generating API bindings for the multicloud services, we use this case study to present our rules of thumb for agile data analytics development.
Michał presents examples with Haskell code and shows how best practices of functional programming solve practical problems of data analytics case-by-case. All cases are naturally motivated and embedded in this case study, but are illustrated with a short Haskell code sample.
The material is aimed at intermediate and expert Haskellers that want to reuse our techniques for other data analytics pipelines, or beginners who want to quickly learn the best monad to use when analysing thousands and millions of records on the input.
YOU MAY ALSO LIKE:
- Lightning Talk: Making and Testing Code Generators in Haskell (SkillsCast recorded in October 2019)
- Data-Driven Improvement of Software Quality with Markus Harrer (Online Course on 15th - 16th November 2021)
- Haskell eXchange 2021: Novice Track (Online Conference on 15th November 2021)
- Haskell eXchange 2021: Pro Track (Online Conference on 16th - 17th November 2021)
- Accessibility Testing: Why and How to involve People with Disabilities (Online Meetup on 28th October 2021)
- Hashing Modulo Alpha Equivalence (SkillsCast recorded in May 2021)
- In The Belly Of The Whale: Tales From Haskell In The Enterprise (SkillsCast recorded in May 2021)
Agile Functional Data Pipeline in Haskell: A Case Study of Multicloud API Binding
Michał got PhD in structural bioinformatics pipelines, and after two postdocs in top research facilities moved on to use his expertise of data analysis platforms in commerce. After a stint in a bank, and fintech startup, he founded his own company.