A checkout service must update an order and retrieve it immediately. This is an operational workload suited to a transactional database.
5 Amazon Redshift in Practice Online Quiz Questions
Use this free practice quiz with 20 questions to review 5 Amazon Redshift in Practice, test your knowledge, and prepare for your next test or exam.
A team is choosing a database for a checkout service that frequently updates individual orders and needs low-latency retrieval. Which option is the best fit?
- A
Use Redshift as the primary database because it is optimized for frequent, low-latency order updates.
- B
Use an operational database suited to application transactions.
- C
Use a data warehouse because checkout updates require aggregating large datasets.
To bulk-load a CSV from S3 into a Redshift table, use the command with an S3 path and an IAM role.
In a sales warehouse, a fact table can record sale events, while dimension tables provide descriptive context such as product or date information.
- A
True
- B
False
An analyst needs quarterly revenue totals spanning several years of orders. Which database is the likely fit for this analytical task?
- A
Use an operational database because quarterly summaries are individual transaction lookups.
- B
Use DynamoDB because the analyst is retrieving a user profile by a known key.
- C
Use Redshift to analyze quarterly revenue across years of orders.
For sale_id 1003 in the sample data, what month and year does its sale_date belong to? Enter the answer in YYYY-MM format.
Which characteristics of Redshift support analytical queries over large datasets? Select all correct choices.
- A
Massively parallel processing
- B
A design focused on frequent, low-latency updates to individual application records
- C
Columnar storage
- D
Compression to help scan and aggregate data efficiently
In a warehouse, fact tables record such as sales, while dimension tables add such as product, customer, or date details.
An application must retrieve a user profile by a known key at scale. Which database is a likely fit when the access pattern matches?
- A
Redshift, because broad analytical scans are the same as key-based profile lookups.
- B
DynamoDB, when its key-value access pattern fits the application.
- C
A data warehouse, because it is optimized for frequent low-latency access to one user profile.
A team is loading a large CSV from S3 into Redshift. Which statements describe an appropriate approach? Select all correct choices.
- A
Use COPY to load the CSV from its S3 location.
- B
Grant no bucket access to Redshift; an IAM role is unnecessary.
- C
Provide an IAM role that permits access to the S3 bucket.
- D
COPY can load data in parallel and is generally more efficient than inserting a large dataset row by row.
A company needs both low-latency checkout updates and reports on revenue across many years of orders. Propose a database design using the appropriate roles for an operational database and Redshift, and explain how the analyst can access the data without placing every large analytical scan on the application’s primary database.
Which NoSQL database does the material suggest considering when an application’s key-value access pattern fits?
- A
Amazon Redshift
- B
DynamoDB
- C
Amazon RDS
- D
Amazon Aurora
True or false: When loading a file from S3 with Redshift's COPY command, the IAM role must permit access to the bucket.
- A
True
- B
False
In the sales table schema, unit_price is defined as DECIMAL(10, 2). How many digits are allowed after the decimal point?
An analyst needs quarterly revenue summaries across years of orders. Which option is the best fit for this analytical workload?
- A
Amazon Redshift
- B
DynamoDB
- C
An operational database optimized for individual transactions
- D
A database chosen only for updating one order at a time
You have a large CSV file in S3 and want to load it into the Redshift sales table efficiently. Which approach should you choose?
- A
Insert every CSV row individually with a separate SQL statement
- B
Use SELECT COUNT(*) to import the CSV
- C
Use COPY to load the CSV from S3
- D
Use GROUP BY to load the CSV from S3
In the described warehouse design, the sales table records individual sales events, while product and customer tables provide descriptive context. What role does sales have?
- A
The
salestable is a dimension table because it contains dates. - B
The
salestable is a fact table because it records sales events. - C
The
salestable is an operational database because its rows are sales. - D
The
salestable is a dimension table because it contains quantities.
To find how many records were loaded into sales, what SQL expression is used inside SELECT in the example count query?
A query selects region and SUM(quantity * unit_price) AS revenue, then groups by region. What does the query report?
- A
It returns one row for each sale, with quantity and unit price unchanged.
- B
It returns total revenue for each region.
- C
It returns the number of sales in each region.
- D
It returns monthly revenue for each product.
In the monthly-by-product query, each result row corresponds to a grouping of which two selected fields? Enter both field names joined by and.
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