## 1 Introduction
### Significance of the Study
Hence, this approach presents a scalable architecture that allows a better adaptation in integrating software units (platforms, applications, and any software system that can be integrated with another) with easy maintenance. The idea is to ameliorate the reduction of cost and time in the integration through low coupling. To achieve this, a Canonical Data Model (CDM) was defined, which, according to the International Business Machines Corporation (IBM), is a well-defined model that structures the information in an organization; the objective is not only limited to modeling the data in a database but serves as a reference for all the entities and their relationships through all the databases that exist in the company and all the legacy applications that contribute to the initiative [3]. This model was extended with Agnostic Messages (AM), which are digital structures representing an unknown entity or process regardless of whether they are used at design or run-time [4]. These messages allow data to be modeled within a single database and serve as a reference for all entities and their relationships, as well as represent standard information produced and consumed by applications [3] in a simplified manner using structures Map collection (key-value structures without duplicated keys). The direct users of this architecture, named the Dynamic Canonical Data Model (DCDM), are architects and software developers in charge of analyzing, proposing, and implementing integration solutions. In this form, they will benefit by allowing an architecture that provides them the much sought-after low coupling between technological architects when proposing integration solutions. The proposed architecture can be applied to the following:  
* The integration from one to different software units, generating data integration between different platforms and systems. * The maintaining of master data integration. Master data is all the data critical to running a business, describing people (customers, employees, and suppliers), places (offices and locations), and things (products and assets) in different repositories. From a single master data point, different platforms and systems are maintained. * Any integration running a Data Manipulation Language (DML) of a database with its respective operations (insert, update, delete, and query). It can be used for data maintenance on different platforms and protocols at runtime. The Dynamic Canonical Data Model architecture presented in this article was developed to satisfy the integration needs of the Mexican Logistics Company Paquetexpress ([[https://www.paquetexpress.com.mx](https://www.paquetexpress.com.mx)]([https://www.paquetexpress.com.mx](https://www.paquetexpress.com.mx)), accessed on 20 May 2023), dedicated to national and international parcel delivery in more than 240 countries around the world. The case was developed in response to the need for the integration of software units, particularly in the case of shipment validations with Amazon ([[https://amazon.com](https://amazon.com)]([https://amazon.com](https://amazon.com)), accessed on 25 May 2023) and Mercadolibre ([[https://mercadolibre.com](https://mercadolibre.com)]([https://mercadolibre.com](https://mercadolibre.com)), accessed on 26 May 2023). The DCDM architecture was designed according to the shortcomings detected in EAI in previous research presented in reference [1]. This was because the integration costs per year represented a high expense for the company. For this reason, a research project was developed in the Information Technology (IT) department and the Postgraduate Program in Applied Informatics at the _Universidad Autonoma de Sinaloa_ ([[https://uas.edu.mx](https://uas.edu.mx)]([https://uas.edu.mx](https://uas.edu.mx)), accessed on 5 June 2023), where the DCDM architecture emerged.