An organization needs to store structured, semi-structured, and unstructured data in its raw, native format in the same repository. Which cloud data management solution should the organization use?
B. Data lake
A data lake is a cloud data management solution that can store structured, semi-structured, and unstructured data in its raw, native format in the same repository. Data lakes are designed to be scalable and flexible, and they can be used to store a wide variety of data
B is the answer.
https://cloud.google.com/learn/what-is-a-data-lake
A data lake is a centralized repository designed to store, process, and secure large amounts of structured, semistructured, and unstructured data. It can store data in its native format and process any variety of it, ignoring size limits.
Per Google docs, "data lake is a centralized repository designed to store, process, and secure large amounts of structured, semi structured, and unstructured data. It can store data in its native format and process any variety of it, ignoring size limits." native format aka raw
https://cloud.google.com/learn/what-is-a-data-lake
d: A data warehouse collects data from various sources, whether internal or external, and optimizes the data for retrieval for business purposes. The data is usually structured, often from relational databases, but it can be unstructured too.
A data lake can store all types of data with no fixed limitation on account size or file and with no specific purpose defined yet. The data comes from disparate sources and can be structured, semi-structured, or even unstructured. Data-lake data can be queried as needed.
A data lake is a centralized repository designed to store, process, and secure large amounts of structured, semistructured, and unstructured data. It can store data in its native format and process any variety of it, ignoring size limits.
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