The current operating model is based on data, understanding it as a raw material whose utility depends on its refinement, processing, and circulation; therefore, in the restaurant, hospitality, and retail sectors, daily activity is dependent on digital devices and limited by the functionalities they provide.
This technological paradigm rewards systemic interoperability, where open digital tools integrate with each other to form a modular and flexible ecosystem tailored to the needs of the business. In contrast, the traditional IT approach, of closed systems, with isolated databases inaccessible from the outside, has become a limiting factor for the business, generating technical obsolescence, hindering team agility, and constraining operations instead of serving them.
Modern software architecture has evolved towards a distributed, multilateral, and systemic approach oriented around the functional needs of the business: a modular suite composed of different digital tools that solve specific problems while exchanging data bidirectionally.
From this reality arises the need to interconnect IT tools so they can operate as part of a cohesive network.
1. Define objectives: Review the goals you want to achieve and the specific challenges you face.
2. Identify the systems: Determine which tools are involved in the integration and which components are part of the operation.
3. Map the information: Define which data will be processed.
4. Evaluate connectivity: Check that each system has an API, and examine its connection possibilities. For systems without an API, investigate if they allow data import/export through files such as CSV, Excel, XML, or JSON.
5. Design data flows: Establish how information will move between tools.
6. Assign roles: For each data point, define which system is considered the source and which is the receiver.
7. Establish the connection: Define how the systems will be connected and, if necessary, create an intermediate layer to act as a bridge.
8. Choose the synchronization type: Define the data exchange ( real-time, event-driven, batch processing, etc. ).
9. Standardize the data: Ensure that the information has a consistent format.
10. Validate incoming data: Implement rules and filters to verify the information received by the target tools.
11. Perform tests: Test the integration using real-case data.
12. Protect operational continuity: Establish security practices, error alerts, and action protocols in case of failure.
13. Deploy: Implement the integration in phases.
14. Monitor: Verify that the processes are working correctly.
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The DX ecosystem
Designed for companies, businesses, and organizations that work with data, seek to extract value from it, or are looking to start doing so, we offer comprehensive support throughout the entire data lifecycle.
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