People use data to enhance their intuition. Whether used to conduct research, train machine learning algorithms, or build a data-driven app, finding, cleaning, and normalizing data is a time consuming, non-value added process.
Datalogue automates that process by leveraging machine learning and distributed computing to find patterns in the structure of datasets and transform them into formats that scientists, developers, and researchers expect. Once transformed, we provide an extensive catalogue of private and public datasets where people can quickly and intuitively find the data they need to enhance applications or research.
Data is messy. People who analyze data spend roughly 80% of their time finding, cleaning, and normalizing it.
Datalogue’s customers are those who use data, the researcher, the developer, and the student, and those who create data.