Dot-Check is a modular, flexible, and fully configurable application for monitoring and validating process data in ERP systems. Developed in Python with Pandas and NumPy, it is entirely controlled via JSON-based configuration files — requiring no hardcoded logic or additional programming.
In this application, process flows are defined through the configuration file. Each status specifies at which stage of the process a record currently resides — whether it has entered a stage, remained on hold, or skipped it altogether. This structure enables a detailed analysis of data movement within organizational processes.
Additionally, based on rules defined in the configuration, data consistency or inconsistency is evaluated. For each record, it is determined whether the data is valid or invalid. In cases of invalidity, the type of error is also identified. This functionality allows precise detection of system errors and facilitates corrective actions.
Key Features of Dot-Check
Fully Configurable JSON-based Architecture – No changes to source code required.
Supported Inputs – Excel and CSV files.
Robust Exception Handling – Ensures program execution continues smoothly under unexpected conditions.
Professional Color-coded Logging – Quickly identifies key messages, warnings, and errors.
Target Users – Data analysts, IT teams, and process managers in organizations using ERP systems.
Dot-Check is designed as a precise, scalable, and flexible analytical tool for monitoring data health and process flow. It enables teams to gain maximum insights into the actual state of their information systems with minimal effort.