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NEW QUESTION: 1
Which statement is false with respect to Dashboards?
A. Prompts on the dashboards can be shared between different pages of a dashboard.
B. Options for the Export and Refresh report links can be enabled globally at the dashboard level.
C. Multiple Analyses can be arranged into different columns and sections with different sizes on a dashboard.
D. All the Analyses placed on a dashboard must be sourced from the same subject area.
NEW QUESTION: 2
Which of the following statements regarding IP address 220.127.116.11 are correct?
A. It is a private IP address.
B. It represents all the routers.
C. It represents all the hosts and routers.
D. It is a multicast IP address.
NEW QUESTION: 3
A company's production application runs online transaction processing (OLTP) transactions on an Amazon RDS MySQL DB instance The company is launching a new reporting tool that will access the same data The reporting tool must be highly available and not impact the performance of the production application.
How can this be achieved?
A. Create hourly snapshots of the production RDS DB instance
B. Create multiple RDS Read Replicas of the production RDS DB instance Place the Read Replicas in an Auto Scaling group
C. Create a Multi-AZ RDS Read Replica of the production RDS DB instance
D. Create a Single-AZ RDS Read Replica of the production RDS DB instance Create a second Single-AZ RDS Read Replica from the replica
Amazon RDS Read Replicas provide enhanced performance and durability for RDS database (DB) instances.
They make it easy to elastically scale out beyond the capacity constraints of a single DB instance for read-heavy database workloads. You can create one or more replicas of a given source DB Instance and serve high-volume application read traffic from multiple copies of your data, thereby increasing aggregate read throughput. Read replicas can also be promoted when needed to become standalone DB instances. Read replicas are available in Amazon RDS for MySQL, MariaDB, PostgreSQL, Oracle, and SQL Server as well as Amazon Aurora.
Amazon RDS Read Replicas Now Support Multi-AZ Deployments
Amazon RDS Read Replicas enable you to create one or more read-only copies of your database instance within the same AWS Region or in a different AWS Region. Updates made to the source database are then asynchronously copied to your Read Replicas. In addition to providing scalability for read-heavy workloads, Read Replicas can be promoted to become a standalone database instance when needed.
Amazon RDS Multi-AZ deployments provide enhanced availability for database instances within a single AWS Region. With Multi-AZ, your data is synchronously replicated to a standby in a different Availability Zone (AZ). In the event of an infrastructure failure, Amazon RDS performs an automatic failover to the standby, minimizing disruption to your applications.
You can now use Read Replicas with Multi-AZ as part of a disaster recovery (DR) strategy for your production databases. A well-designed and tested DR plan is critical for maintaining business continuity after a disaster. A Read Replica in a different region than the source database can be used as a standby database and promoted to become the new production database in case of a regional disruption.
NEW QUESTION: 4
A telecommunications company needs to predict customer churn (i.e. customers eho decide to switch a computer). The company has historic records of each customer, including monthly consumption patterns, calls to customer service, and whether the customer ultimately quit th eservice. All of this data is stored in Amazon S3. The company needs to know which customers are likely going to churn soon so that they can win back their loyalty.
What is the optimal approach to meet these requirements?
A. Use the Amazon Machine Learning service to build the binary classification model based on the dataset stored in Amazon S3. The model will be used regularly to predict churn attribute for existing customers
B. Use a Redshift cluster to COPY the data from Amazon S3. Create a user Define Function in Redshift that computers the likelihood of churn
C. Use EMR to run the Hive queries to build a profile of a churning customer. Apply the profile to existing customers to determine the likelihood of churn
D. Use AWS QuickSight to connect it to data stored in Amazon S3 to obtain the necessary business insight. Plot the churn trend graph to extrapolate churn likelihood for existing customer