A large energy company is using Amazon QuickSight to build dashboards and report the historical usage data of its customers. This data is hosted in Amazon Redshift. The reports need access to all the fact tables' billions of records to create aggregation in real time, grouping by multiple dimensions.
A data analyst created the dataset in QuickSight by using a SQL query and not SPICE. Business users have noted that the response time is not fast enough to meet their needs.
Which action would speed up the response time for the reports with the LEAST implementation effort?
A. Use QuickSight to modify the current dataset to use SPICE.
B. Use AWS Glue to create an Apache Spark job that joins the fact table with the dimensions. Load the data into a new table.
C. Use Amazon Redshift to create a materialized view that joins the fact table with the dimensions.
D. Use Amazon Redshift to create a stored procedure that joins the fact table with the dimensions. Load the data into a new table.
A data analyst created the dataset in QuickSight by using a SQL query and not SPICE. Business users have noted that the response time is not fast enough to meet their needs.
Which action would speed up the response time for the reports with the LEAST implementation effort?
A. Use QuickSight to modify the current dataset to use SPICE.
B. Use AWS Glue to create an Apache Spark job that joins the fact table with the dimensions. Load the data into a new table.
C. Use Amazon Redshift to create a materialized view that joins the fact table with the dimensions.
D. Use Amazon Redshift to create a stored procedure that joins the fact table with the dimensions. Load the data into a new table.