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Whereas a data warehouse will need rigid datamodeling and definitions, a data lake can store different types and shapes of data. In a data lake, the schema of the data can be inferred when it’s read, providing the aforementioned flexibility. However, this flexibility is a double-edged sword.
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data # Assing local directory path to a python variable local_data_path = ". . By using the flexible document datamodel of MongoDB Atlas, organizations can represent and query complex knowledge entities and their relationships within Amazon Bedrock.
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