A retail company wants to implement a data warehouse on Google Cloud to store large volumes of historical transaction data from multiple stores. The data will be used to perform analytics, generate insights, and support dashboards with complex queries involving aggregations, filtering, and joining large tables. The solution should be cost-effective for storing historical data and optimized for analytics. Which storage solution would be the best choice?
You are tasked with moving a large volume of data (around 50 TB) from an on-premises data center to Cloud Storage for analysis. Due to limited internet bandwidth and a strict deadline, you need a solution that allows you to transfer the data efficiently and securely with minimal disruption to regular network activities. Which two of the following Google Cloud tools would be most suitable for this scenario? (Select two)
You are tasked with moving a large volume of data (around 50 TB) from an on-premises data center to Cloud Storage for analysis. Due to limited internet bandwidth and a strict deadline, you need a solution that allows you to transfer the data efficiently and securely with minimal disruption to regular network activities. Which two of the following Google Cloud tools would be most suitable for this scenario? (Select two)
You have a model registered in the Model Registry in Vertex AI and need to evaluate its performance over multiple versions for A/B testing in production. Which approach will best allow you to manage different versions effectively while ensuring they can be accessed and deployed as needed?
A retail business analyst needs to create a dashboard in Looker to monitor the weekly sales performance across various product categories. The business stakeholders require a single-view dashboard that shows key performance metrics such as total revenue, average order value, and weekly growth rates. Which action should the analyst take to best meet these business requirements in Looker?