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This reservoir acts as a massive storage space where all data drops are accumulated. Just as water collection requires a dam to prevent overflow and make gathering feasible, data collection involves consolidating dispersed data sources into a centralized repository to enable efficient processing and analysis.

From Data Lake to Data Warehouse

Once stored in the data lake, the collected data often undergoes a filtering and processing stage, akin to water treatment in purification plants. This step involves cleaning, transforming, and organizing raw data into a more structured format, known as a Data Warehouse.