about us
Our story
From Observation to Innovation: An Evidence-Based Approach​
"Moodules was founded on a simple observation: many talented data analysts and scientists are spending too much time wrestling with repetitive coding tasks, rather than extracting insights. Based on our experiece, as well as our observations of other data professionals, we have identified distinct categories of tasks that make up a typical data analytics workflow. This insight became the foundation of our modular approach."
- Ruslan Jabrayilov, founder of Moodules
Tasks that make up a typical data analytics workflow
% of people who report having difficulties with the task or find it repetitive and time consuming
Importing files
87%
This includes navigating complex project directories to find neccessary files, generating Pandas code for importing multiple files simultaneously, figuring out which tabs to load from Excel files as well as determining separators for CSV files
Preprocessing datasets
96%
Includes tasks such as viewing datasets eifficiently once they are imported as well as seeing their shape (e.g., head, tail). Other tasks include preprocessing datasets, such as filtering columns and/or rows, merging, concatenating datasets etc.
Visualizing results
90%