The art of unlocking companies’ siloed data, by using automatic or manual connections, by transforming system data into business features or parameters, but also by cleansing and consolidating data into one or more meaningful data repositories.
What we do
Data is typically stored in different systems; in most cases fast & connected data needs aggregating with slow & disconnected sources in order to research specific questions or to set-up workflows.
data model design
Not all research questions can be answered using the provided data models; therefore new models might need to be designed in order to start researching the data.
data transformations & cleansing
Data is stored in systems for a specific purpose; in order to research cause-and-effect relationships, data needs transformation and cleansing.
Typical transactional and/or business-specific data needs to be translated into parameters and features that will be used in the statistical data modeling.