# Data Conversion Strategies for Effective Aviation Technical Support as a Service
## 2 Alternative ATSaaS Platform Architectures
### Decentralized ATSaaS Platform Architecture  
In a decentralized architecture, each organization is responsible for converting its data into the required format before transmitting it to the ATSaaS provider. This model relies on standardized data exchange protocols and interfaces that client organizations must implement locally. The data flow diagram for the decentralized ATSaaS platform architecture (Figure 3) shows a distributed processing system where data flow through both local and centralized components. At the local level, multiple parallel processing streams exist--one for each airline. Each local stream follows the same pattern: data flow from the airline source through local data generation, then through local conversion, resulting in standardized format output. All these standardized local outputs then converge into the central ATSaaS platform, entering through a single validation process. Within the platform, the validated data flow into the central standardized DB, then through the data processing engine, and finally through the report generation process to produce standardized reports. Advantages of decentralized architecture: By decentralizing the data conversion process, the risk is distributed across multiple organizations. A failure in one organization's system does not affect the entire ATSaaS network. Local data conversion can facilitate real-time data transmission and availability, as there is no need for data to travel to a central hub for processing. Each organization can tailor the data conversion process to meet its specific needs and requirements, allowing for greater flexibility and customization. Decentralizing data conversion reduces the load on the central ATSaaS infrastructure, potentially lowering the provider's operational costs and improving system performance. Figure 3: Data flow diagram for the decentralized ATSaaS platform architecture. Disadvantages of decentralized architecture:
* Each organization must implement and maintain its data conversion mechanisms, which can be complex and resource intensive. This approach requires significant coordination and standardization efforts. * Decentralized data conversion can lead to inconsistencies in data quality and format, especially if organizations do not adhere strictly to the standardized protocols. To prevent such issues, it will be necessary to establish clear standards and requirements for input data. However, this will significantly increase the complexity of system development and make integration more challenging for clients. Decentralized data conversion, without strict adherence to standardized protocols, risks inconsistencies in data quality and format. * Ensuring the security of data during transmission from multiple decentralized locations can be challenging. Each organization must implement robust security measures, increasing the overall complexity of the system. * While decentralized systems may reduce long-term operational costs, the initial setup costs for each organization to implement the necessary data conversion infrastructure can be high. In the decentralized ATSaaS architecture (Figure 3), local processing plays a crucial role in data conversion, validation, and security at the participant level. Unlike the centralized model, where the ATSaaS provider manages data conversion within a unified platform, in a decentralized setup, each participant (e.g., small airlines, MRO providers, and parts suppliers) is responsible for implementing and maintaining its own local processing capabilities. This means that the cost of local processing infrastructure--such as computing power, software, data validation mechanisms, and security compliance--falls primarily on individual participants rather than the ATSaaS provider. However, while decentralized processing shifts computational responsibility away from the central platform, it also introduces variability in system implementation and security standards among participants, which could increase integration and interoperability challenges.