Question-21: The term data lake refers to a centralised repository that is designed to store, process, and safeguard massive amounts of data that may be organised, semistructured, or unstructured. The phrase data warehouse may also be used to refer to this kind of data storage, as can data warehouse lake. It is able to handle any kind of data, regardless of its size, and store data in the format in which it was originally created. Additionally, it is able to store data in the format in which it was originally created. Your company is in the process of designing its data lake on Google Cloud, and it wants to develop a number of different ingestion pipelines in order to collect unstructured data from a variety of sources. After the data has been uploaded to Google Cloud, it will be processed in a variety of data pipelines in order to build a recommendation engine that end users of the website will have access to using. The structure of the data that is acquired from the source systems may be susceptible to modification at any time that is convenient for the researchers. It is essential that the data be preserved in the exact same format in which it was collected if reprocessing is to be performed. In the event that the data structure is incompatible with the processing pipelines that are presently being used, this step is essential. After you have completed the process of acquiring the data, the next step will be to develop an architecture that can accommodate the use case. What course of action do you recommend taking?
A. First run the data through the processing pipeline, and then store the processed data in a table in BigQuery so that it may be used in a subsequent pass through the pipeline.
B. You need to use BigQuery to organize the information into a table. Build the processing pipelines that will allow you to get the data from the table after it has been loaded.
C. Send the data through the processing pipeline, and then when it has been processed, store it in a bucket within a cloud storage service so that it may be reprocessed at a later time.
D. Upload the files to a cloud storage provider and place them in a folder or bucket. Develop the processing pipelines that will be used to extract the data from the bucket after they have been developed.

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