Architectural flexibility can support system data quality in several ways:
1. Scalability: A flexible architecture allows for scaling up or down resources as required. This ensures that the system can handle an increase in data volume and complexity without compromising data quality.
2. Data Integration: A flexible architecture enables the integration of different data sources seamlessly, thus ensuring high-quality data.
3. Customization: A flexible architecture provides the ability to customize the system, thereby ensuring that it meets the unique data quality requirements of different businesses.
4. Automation: A flexible architecture enables the automation of data quality checks, improving data consistency and accuracy.
5. Collaboration: A flexible architecture allows for collaboration among different teams, ensuring the sharing of best practices and knowledge, which ultimately improves data quality.
By adopting a flexible architecture, organizations can ensure that their system is designed to support data quality, ultimately resulting in better decision-making and improved business outcomes.
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