Data ingestion architecture refers to the framework and processes involved in collecting, importing, and processing data from various sources into a data storage system for analysis and reporting. This architecture is crucial for organizations that rely on data-driven decision-making, as it ensures that data is efficiently and accurately captured in real-time or batch modes. Key components of data ingestion architecture include data sources, ingestion methods (such as Change Data Capture or streaming), and storage solutions (like data lakes or data warehouses). A well-designed architecture enhances data accessibility, quality, and usability for analytics and business intelligence.