DataFlow is a modular and extensible tool designed to automate complex data processing pipelines - from raw measurements to research-ready datasets. In many projects, incoming data requires multiple filtering, transformation, and validation steps. DataFlow enables users to define these steps as modular components - such as data importers, filters, or converters - which can be flexibly adapted to different data types and formats. Once configured, pipelines run automatically as new data arrives on a connected server, processing it through each stage and storing results in a central database. Researchers can visualize the data at every processing stage, apply mutations such as flagging or smoothing, and access only quality-assured datasets. A built-in account and permission system ensures controlled data access and integrity. By streamlining these steps, DataFlow significantly reduces the manual effort of data preparation and promotes reproducible, shareable research data across teams.