Professional-Cloud-Architect Practice Online

A company wants to build a data processing pipeline that ingests data from various sources, transforms the data, and then stores the processed data in a data warehouse for analysis. The pipeline should be scalable, easy to manage, and able to handle changes in data sources and data processing requirements. How would you design this data processing pipeline using Google Cloud services?

In your role as a cloud architect, you're preparing to transition your on-site data warehouse to Google Cloud, utilizing BigQuery. You have to create a presentation for the management team to explain the cost structure of BigQuery. There are two primary elements to consider when it comes to the pricing of BigQuery. Select the costs you incur when using BigQuery.

In your customer support tool, all email and chat conversations are logged to Bigtable for storage and analysis purposes. However, to ensure data privacy and compliance, it is essential to sanitize this data by removing any Personally Identifiable Information (PII) or payment card information before it is initially stored. What approach would you recommend for accomplishing this task?

You have a Compute Engine managed instance group that adds and removes Compute Engine instances from the group in response to the load on your application. The instances have a shutdown script that removes REDIS database entries associated with the instance. You see that many database entries have not been removed, and you suspect that the shutdown script is the problem. You need to ensure that the commands in the shutdown script are run reliably every time an instance is shut down. You create a Cloud Function to remove the database entries. What should you do next?

You are designing a Data Warehouse on Google Cloud and want to store sensitive data in BigQuery. Your company requires you to generate the encryption keys outside of Google Cloud. You need to implement a solution. What should you do?