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NEW QUESTION: 1
Note: The question is part of a series of questions that use the same or similar answer choices. An answer choice may be correct for more than one question in the series. Each question is independent of the other question in the series. Information and details provided in a question apply only to that question.
You have a reporting database that includes a non-partitioned fact table named Fact_Sales. The table is persisted on disk.
Users report that their queries take a long time to complete. The system administrator reports that the table takes too much space in the database. You observe that there are no indexes defined on the table, and many columns have repeating values.
You need to create the most efficient index on the table, minimize disk storage and improve reporting query performance.
What should you do?
A. Create a nonclustered filtered index on the table.
B. Create a nonclustered columnstore index on the table.
C. Create a nonclustered index on the table.
D. Create a clustered indexon the table.
E. Create a hash index on thetable.
F. Create a clustered columnstore index on the table.
Answer: F
Explanation:
Explanation
The columnstore index is the standard for storing and querying large data warehousing fact tables. It uses column-based data storage and query processing to achieve up to 10x query performance gains in your data warehouse over traditional row-oriented storage, and up to 10x data compression over the uncompressed data size.
A clustered columnstore index is the physical storage for the entire table.

NEW QUESTION: 2
Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution.
After you answer a question in this scenario, you will NOT be able to return to it. As a result, these questions will not appear in the review screen.
You are developing a solution that will use Azure Stream Analytics. The solution will accept an Azure Blob storage file named Customers. The file will contain both in-store and online customer details. The online customers will provide a mailing address.
You have a file in Blob storage named LocationIncomes that contains based on location. The file rarely changes.
You need to use an address to look up a median income based on location. You must output the data to Azure SQL Database for immediate use and to Azure Data Lake Storage Gen2 for long-term retention.
Solution: You implement a Stream Analytics job that has one streaming input, one reference input, two queries, and four outputs.
Does this meet the goal?
A. No
B. Yes
Answer: B
Explanation:
Explanation
We need one reference data input for LocationIncomes, which rarely changes.
We need two queries, on for in-store customers, and one for online customers.
For each query two outputs is needed.
Note: Stream Analytics also supports input known as reference data. Reference data is either completely static or changes slowly.
References:
https://docs.microsoft.com/en-us/azure/stream-analytics/stream-analytics-add-inputs#stream-and-reference-inpu
https://docs.microsoft.com/en-us/azure/stream-analytics/stream-analytics-define-outputs

NEW QUESTION: 3
The vxassist convert command can be used to convert between which two volume layouts? (Select two.)
A. mirror-stripe to stripe-mirror
B. mirror-stripe to RAID-5
C. concat-mirror to concat
D. concat-mirror to mirror-concat
E. mirror-stripe to stripe
Answer: A,D

NEW QUESTION: 4
All of the following are causes of Cholecystitis except:
A. Fertility
B. Female
C. Bile duct obstruction
D. Obesity
Answer: C
Explanation:
Explanation: All of the following are causes of Cholecystitis except bile duct obstruction. Cholecystitis can result in the obstruction of bile duct due to the presence of stones. So Bile duct obstruction is due to the cholecystitis and the other three factors are predisposes to stones, and thus to cholecystitis. This is more relatively common in overweight women.