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NEW QUESTION: 1
Note: This question is part of a series of questions that use the same scenario. For your convenience, the scenario is repeated in each question. Each question presents a different goal and answer choices, but the text of the scenario is exactly the same in each question in this series.
You have a Microsoft SQL Server data warehouse instance that supports several client applications.
The data warehouse includes the following tables: Dimension.SalesTerritory, Dimension.Customer, Dimension.Date, Fact.Ticket, and Fact.Order. The Dimension.SalesTerritory and Dimension.Customer tables are frequently updated. The Fact.Order table is optimized for weekly reporting, but the company wants to change it daily. The Fact.Order table is loaded by using an ETL process. Indexes have been added to the table over time, but the presence of these indexes slows data loading.
All data in the data warehouse is stored on a shared SAN. All tables are in a database named DB1. You have a second database named DB2 that contains copies of production data for a development environment. The data warehouse has grown and the cost of storage has increased. Data older than one year is accessed infrequently and is considered historical.
You have the following requirements:
You are not permitted to make changes to the client applications.
You need to optimize the storage for the data warehouse.
What change should you make?
A. Remove the historical data from the database to leave available space for new data.
B. Partition the Fact.Order table, and move historical data to new filegroups on lower-cost storage.
C. Move historical data to new tables on lower-cost storage.
D. Create new tables on lower-cost storage, move the historical data to the new tables, and then shrink the database.
Answer: B
Explanation:
Explanation
Create the load staging table in the same filegroup as the partition you are loading.
Create the unload staging table in the same filegroup as the partition you are deleteing.
From scenario: Data older than one year is accessed infrequently and is considered historical.
References:
https://blogs.msdn.microsoft.com/sqlcat/2013/09/16/top-10-best-practices-for-building-a-large-scale-relational-d

NEW QUESTION: 2
You are developing an application. You use an instance of the ConfigurationBuilder class to retrieve user secrets, configuration strings, and other sensitive variables on your development device.
You add new features to the application.
You need to retrieve application secrets.
What should you implement? To answer, drag the appropriate technologies to the correct configuration options. Each technology may be used once, more than once, or not at all. You may need to drag the split bar between panes or scroll to view content.
NOTE: Each correct selection is worth one point.

Answer:
Explanation:

Explanation

Box 1: Secret Manager tool
Box 2: Environment variables
Box 3: Microsoft Azure Key Vault
References:
https://docs.microsoft.com/en-us/aspnet/core/security/app-secrets?view=aspnetcore-2.1&tabs=visual-studio
https://www.humankode.com/asp-net-core/asp-net-core-configuration-best-practices-for-keeping-secrets-out-of-s

NEW QUESTION: 3
You develop data engineering solutions for a company. You must migrate data from Microsoft Azure Blob storage to an Azure SQL Data Warehouse for further transformation. You need to implement the solution.
Which four actions should you perform in sequence? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order.

Answer:
Explanation:

Explanation

Step 1: Provision an Azure SQL Data Warehouse instance.
Create a data warehouse in the Azure portal.
Step 2: Connect to the Azure SQL Data warehouse by using SQL Server Management Studio Connect to the data warehouse with SSMS (SQL Server Management Studio) Step 3: Build external tables by using the SQL Server Management Studio Create external tables for data in Azure blob storage.
You are ready to begin the process of loading data into your new data warehouse. You use external tables to load data from the Azure storage blob.
Step 4: Run Transact-SQL statements to load data.
You can use the CREATE TABLE AS SELECT (CTAS) T-SQL statement to load the data from Azure Storage Blob into new tables in your data warehouse.
References:
https://github.com/MicrosoftDocs/azure-docs/blob/master/articles/sql-data-warehouse/load-data-from-azure-blob

NEW QUESTION: 4
You are creating a SQL Server Analysis Services (SSAS) multidimensional database.
Users need a time dimension for:
Dates

Delivery dates

Ship dates

You need to implement the minimum number of required SSAS objects.
What should you do?
A. Add a measure that uses the DistinctCount aggregate function to an existing measure group.
B. Add a measure that uses the LastNonEmpty aggregate function. Use a regular relationship between the time dimension and the measure group.
C. Add a calculated measure based on an expression that counts members filtered by the Exists and NonEmpty functions.
D. Create a new named calculation in the data source view to calculate a rolling sum. Add a measure that uses the Max aggregate function based on the named calculation.
E. Add a measure that uses the Count aggregate function to an existing measure group.
F. Use role playing dimensions.
G. Add a measure group that has one measure that uses the DistinctCount aggregate function.
H. Create a dimension with one attribute hierarchy. Set the IsAggregatable property to False and then set the DefaultMember property. Use a many-to-many relationship to link the dimension to the measure group.
I. Create a dimension. Create regular relationships between the cube dimension and the measure group.
Configure the relationships to use different dimension attributes.
J. Use the Business Intelligence Wizard to define dimension intelligence.
K. Create several dimensions. Add each dimension to the cube.
L. Create a dimension with one attribute hierarchy. Set the IsAggregatable property to False and then set the DefaultMember property. Use a regular relationship between the dimension and measure group.
M. Add a hidden measure that uses the Sum aggregate function. Add a calculated measure aggregating the measure along the time dimension.
N. Create a dimension with one attribute hierarchy. Set the ValueColumn property, set the IsAggregatable property to False, and then set the DefaultMember property. Configure the cube dimension so that it does not have a relationship with the measure group. Add a calculated measure that uses the MemberValue attribute property.
O. Create a dimension. Then add a cube dimension and link it several times to the measure group.
Answer: F