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.
Talks I've Given
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Agile Functional Data Pipeline in Haskell: A Case Study of Multicloud API Binding
Featuring Michał Gajda
In this case study, Michał discusses making a data pipeline for multicloud API bindings in Haskell for analysis and Python for scraping. He'll introduce a few rules settled on along the way that allow for blinding fast development of agile data analytics.
haskell data-analytics case-study python api-binding multicloud -
Lightning Talk: Making and Testing Code Generators in Haskell
Featuring Michał Gajda
Michał and the Migamake Pte Ltd team are currently making an open source library to help produce code generators in Haskell. It facilitates generating code with syntax-checked templates and unit testing with smaller and more robust tests Michał will go through code generation approaches seen in...
haskell generators -
Automating Elaborate-Transform-Load for Busy Data Scientists
Featuring Michał Gajda
Haskell is making great strides into processing data at greater convenience. You do not only have fast parsers for most important languages, but now automatic parser generators that discover the structure of our documents and package them as Haskell types: DataFrames, JSON Autotype, XML TypeLift....
data haskell parsing csv etl metadata ingest xml json bigdata analytics datascience