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Answer: Store the raw social media posts in Cloud Storage, and write the data extracted from the API into BigQuery.
The correct answer is C. Storing the raw social media posts in Cloud Storage allows for efficient long-term archival and reprocessing, which can handle various data formats such as text, images, and videos. Writing the data extracted from the API into BigQuery enables efficient and scalable analysis, as well as integration with visualization tools like Google Data Studio for creating dashboards. This setup achieves the goal of analyzing posts daily at a low cost with minimal steps while meeting the requirement for archiving raw posts.
Author: LeetQuiz Editorial Team
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You are tasked with analyzing a substantial volume of social media posts on a daily basis. Your primary objectives include achieving this with minimal cost and using the fewest steps possible. Here are your specific requirements: ✑ Batch-load hundreds of thousands of social media posts once per day. ✑ Utilize the Cloud Natural Language API to process these posts to extract topics and sentiment. ✑ Store the raw social media posts for archiving and potential reprocessing needs. ✑ Develop and share dashboards with stakeholders both within and outside the organization. Given these requirements, you need to determine the most effective strategy for storing the data extracted from the Cloud Natural Language API for analysis, in addition to archiving the raw social media posts for historical reference. What approach should you take?
A
Store the social media posts and the data extracted from the API in BigQuery.
B
Store the social media posts and the data extracted from the API in Cloud SQL.
C
Store the raw social media posts in Cloud Storage, and write the data extracted from the API into BigQuery.
D
Feed to social media posts into the API directly from the source, and write the extracted data from the API into BigQuery.
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