# Simplification du Processus Data : Analyse d’Architecture
> Découvrez une analyse des défis de l'architecture data héritée : goulots d'étranglement, performance de production et maintenance complexe des données.

Tags: data-architecture, data-process, big-data, business-intelligence, data-warehouse, performance-it, legacy-systems, management-it
## Slide 1: Data Process Simplification
* Analysis of Legacy Architecture and Challenges.

## Slide 2: Input Sources: The Dual Stream
* Disparate data ingestion with parallel streams for different operational entities (AF & KL).
* Creates duplication in the workflow structure.

## Slide 3: The Bottleneck: 'Coupons Issued'
* Centralization point where all ODS and external Data Warehouse inputs merge.
* Becomes a critical dependency for the entire system.

## Slide 4: Hidden Complexity: Multiple Dependencies
* Key dependencies identified: DWH PNR (Passenger Name Record), DWH TRAFFIC Data, and DWH KL Specifics.

## Slide 5: The Old Process: Full Architecture
* Workflow overview: Sirax -> ODS -> COUPONS ISSUED -> SALES TABLES -> Sales Universe BO.

## Slide 6: Issue 1: Production Performance
* Critical latency and data availability delays caused by serialization through a single bottleneck.

## Slide 7: Issue 2: Lack of Clarity
* The 'Black Box' effect: monolithic design makes error tracing and data lineage difficult.

## Slide 8: Issue 3: Maintenance Nightmare
* Changes in 'Coupons Issued' logic risk breaking downstream Business Objects (BO) dependencies.

## Slide 9: Operational Health Assessment
* Current state scores (out of 10):
    * Process Efficiency: 2.5
    * System Stability: 4
    * Maintenance Speed: 3

## Slide 10: The Path Forward
* Necessity of simplification for scalability, speed, and reliability.
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