Choosing the right data architecture when integrating analytics tools into a tech stack depends on various factors, including existing data availability, structure, and analytics needs. A flexible data architecture serves as a strategic asset that impacts product decisions, scalability, and responsiveness. It is essential to establish a centralized source of truth for data accuracy and to ensure that all data sources are unified and verified. Companies have various options for data collection and integration, such as using existing data warehouses, Customer Data Platforms, or server-side SDKs, each with its own advantages and limitations. A hybrid approach, combining different data ingestion methods, can provide flexibility and scalability. As organizations mature, their data architecture must evolve, accommodating new use cases and technologies while maintaining governance and security standards. Building a data architecture that is trustworthy, comprehensive, and maintainable ensures that analytics tools like Mixpanel can effectively support decision-making and future growth, making data accessible and useful for product teams.