An organization has collected petabytes of historical data. They need an advanced analysis solution that is fast, scalable, and fully managed. Which Google product or service should the organization use?
A. BigQuery.
BigQuery is a fully-managed, serverless, and highly scalable data warehouse designed for analyzing large datasets, including petabytes of historical data. It allows for fast and efficient querying, making it ideal for advanced analytics and handling massive datasets. BigQuery can process vast amounts of data quickly without the need for the organization to manage infrastructure or worry about scaling.
Why the other options are incorrect:
B. Cloud SQL: Cloud SQL is a fully-managed relational database service that supports MySQL, PostgreSQL, and SQL Server. It is great for transactional applications (OLTP) and structured data but is not designed to handle large-scale analytical workloads or petabytes of data. Cloud SQL is more suitable for smaller-scale databases, not for advanced analytics on vast amounts of historical data.
C. Firestore: Firestore is a NoSQL document database primarily used for building scalable and real-time applications, such as mobile and web apps. While it is a flexible and scalable database, it is not designed for large-scale data analytics or data warehousing. It is optimized for document storage and retrieval, not for running complex analytical queries on petabytes of historical data.
D. Cloud Storage: Cloud Storage is an object storage service designed for storing unstructured data such as images, videos, backups, and logs. While it is scalable and cost-effective for storing large volumes of data, it does not provide the necessary tools for advanced analysis or querying of the data. To perform analytics on data stored in Cloud Storage, you would typically need to use a service like BigQuery to query the data.
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