Answer.

Background:

In recent years, the demand for integration solutions has increased, where transparent documentation of data processing and transmission rules is essential, especially when using external services and artificial intelligence. Unformalized data and the lack of clear business rules lead to errors and incidents.

Problem:

The application of AI and external services requires explicitly described rules for working with data: what to send, how to validate, what to do in case of failure, how to log actions, what to return to the user. Without formal descriptions of these rules, technical and business risks increase.

Solution:

The following methodologies are used:

UML Activity Diagram and BPMN for visualizing flows, input and output data
Data Flow Diagram (DFD) for documenting information routes
Decision tables with clear definitions of conditions and actions
Glossaries for a unified dictionary of system and business terms
Specification by Example — formalization through specific user/system scenarios

Key Features:

Explicit separation of system and business rules
Support for tracing from the source to the point of data consumption
Formalization in a single registry and constant updating of these rules

Tricky Questions.

Is it enough to rely solely on diagrams for describing data processing rules?

No, diagrams alone are insufficient. Textual descriptions, condition tables, and examples are necessary to minimize ambiguities.

Is it necessary to document negative scenarios (failures, errors) when working with integrations?

Yes, absolutely! Without such scenarios, it is impossible to foresee proper error handling and ensure SLA.

Is it sufficient to use only technical terminology when formalizing data processing rules?

No, for transparency and proper interaction, it is essential to use a glossary and connect business and technical terms.

Common Mistakes and Anti-Patterns

Describing only happy path scenarios without negative and edge cases
Insufficiently clear decomposition of rules, mixing access control logic, validation, and business logic
Lack of a single repository for formalized rules

Real-Life Example

Negative case:

Integration with a cloud document recognition service. The system analyst described only the basic exchange and missed edge cases (for example, response waiting time, return of invalid data, format validation errors).

Pros:

Rapid progress during the pilot phase

Cons:

Mass incidents after launch due to unhandled errors, unstable performance

Positive case:

The analyst documented not only the happy path but also all edge and exceptional scenarios, created a unified decision table for processing rules. Conducted a series of workshops, refined the glossary of terms among the AI team and technical support staff.