Easily Pass 70-463 Exam With Lead2pass Latest Microsoft 70-463 Brain Dumps (71-80)
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Drag and Drop Questions
You are creating a sales data warehouse. When a product exists in the product dimension, you update the product name. When a product does not exist, you insert a new record. In the current implementation, the DimProduct table must be scanned twice, once for the insert and again for the update. As a result, inserts and updates to the DimProduct table take longer than expected. You need to create a solution that uses a
single command to perform an update and an insert. How should you use a MERGE T-SQL statement to accomplish this goal?
(To answer, drag the appropriate answer choice from the list of options to the correct location or locations in the answer area. You may need to drag the split bar between panes or scroll to view content.)
You are designing a data warehouse for a fresh food distribution business that stores sates by individual product. It stores sales targets by product category. Products are classified into subcategories and categories.
Each product is included in only a single product subcategory, and each subcategory is included in only a single category. The data warehouse will be a data source for an Analysis Services cube. The data warehouse contains two fact tables:
– factSales, used to record daily sales by product
– factProductTarget, used to record the monthly sales targets by product category
Reports must be developed against the warehouse that reports product sales by product, category and subcategory, and product sales targets.
You need to design the product dimension. The solution should use as few tables as possible while supporting all the requirements. What should you do?
A. Create two product tables, dimProduct and dimProductCategory. Connect factSales to dimProduct and factProductTarget to dimProductCategory with foreign key constraints.Direct the cube developer to use key granularity attributes.
B. Create one product table, dimProduct, which contains product detail, category, and subcategory columns. Connect factSales to dimProduct with a foreign key constraint. Direct the cube developer to use a non-key granularity attribute for factProductTarget.
C. Create three product tables, dimProduct, dimProductCategory, and dimProductSubcategory, and a fourth bridge table that joins products to their appropriate category and subcategory table records with foreign key constraints. Direct the cube developer to use key granularity attributes.
D. Create three product tables, dimProduct, dimProductCategory, and dimProductSubcategory.Connect factSales to all three product tables and connect factProductTarget to dimProductCategory with foreign key constraints. Direct the cube developer to use key granularity attributes.
You are reviewing the design of a student dimension table in an existing data warehouse hosted on SQL Azure. The current dimension design does not allow the retention of historical changes to student attributes such as ParentOccupation.
You need to redesign the dimension to enable the full historical reporting of changes to multiple student attributes including ParentOccupation.
What should you do?
A. Add CurrentValue and PreviousValue columns to the student dimension.
B. Enable Snapshot Isolation on the data warehouse.
C. Add an IsCurrent column to the student dimension.
D. Add StartDate and EndDate columns to the student dimension.
You are reviewing the design of an existing fact table named factSales, which is loaded incrementally from a SQL Azure database by a SQL Server Integration Services (SSIS) package each hour. The fact table has approximately 4 billion rows and is dimensioned by product, sales date, and sales time of day.
The database administrator is concerned about the rapid growth of the database and users experience poor reporting performance against this database. Reporting requirements have recently changed and the only remaining report that uses this fact table reports sales by product name, sale month, and sale year. No other reports will be created against this table.
You need to reduce the report processing time and minimize the growth of the database.
What should you do?
A. Create an indexed view over the fact table to sum orderTotal by month.
B. Create a view over the fact table to sum orderTotal by month.
C. Change the granularity of the fact table to month.
D. Partition the fact table by productKey.
You are designing an enterprise star schema that will consolidate data from three independent data marts. One of the data marts is hosted on SQL Azure. Most of the dimensions have the same structure and content. However, the geography dimension is slightly different in each data mart.
You need to design a consolidated dimensional structure that will be easy to maintain while ensuring that all dimensional data from the three original solutions is represented.
What should you do?
A. Create a conformed dimension for the geography dimension.
B. Implement change tracking.
C. Create a degenerate dimension for the geography dimension.
D. Create a Type 2 slowly changing dimension for the geography dimension.
You are adding a new capability to several dozen SQL Server Integration Services (SSIS) packages. The new capability is not available as an SSIS task.
Each package must be extended with the same new capability.
You need to add the new capability to all the packages without copying the code between packages.
What should you do?
A. Use the Expression task.
B. Use the Script task.
C. Develop a custom task.
D. Use the Script component,
E. Develop a custom component.
You are creating a SQL Server Integration Services (SSIS) package to retrieve product data from two different sources. One source is hosted in a SQL Azure database. Each source contains products for different distributors. Products for each distributor source must be combined for insertion into a single product table destination.
You need to select the appropriate data flow transformation to meet this requirement.
Which transformation types should you use?
(Each answer represents a complete solution. Choose all that apply.)
A. Slowly Changing Dimension
D. Union All
Drag and Drop Question
A SQL Server Integration Services (SSIS) project has been deployed to the SSIS catalog.
The project includes a project Connection Manager to connect to the data warehouse.
The SSIS catalog includes two Environments:
Each Environment defines a single Environment Variable named ConnectionString of type string. The value of each variable consists of the connection string to the test or production data warehouses.
You need to execute deployed packages by using either of the defined Environments.
Which three 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.)
Drag and Drop Questions
You are developing a SQL Server Integration Services (SSIS) package that imports data into a data warehouse.
You are developing the part of the SSIS package that populates the ProjectDates dimension table. The business key of the ProjectDates table is the ProjectName column.
The business user has given you the dimensional attribute behavior for each of the four columns in the ProjectDates table.
ExpectedStartDate – New values should be tracked over time.
ActualStartDate – New values should not be accepted.
ExpectedEndDate – New values should replace existing values.
ActualEndDate – New values should be tracked over time.
You use the SSIS Slowly Changing Dimension Transformation.
You must configure the Change Type value for each source column.
Which Change Type values should you select?
(To answer, drag the appropriate value from the list of values to the correct location or locations in the answer area.)
You are designing a SQL Server Integration Services (SSIS) data flow to load sales transactions from a source system into a data warehouse hosted on SQL Azure. One of the columns in the data source is named ProductCode. Some of the data to be loaded will reference products that need special processing logic in the data flow.
You need to enable separate processing streams for a subset of rows based on the source product code.
Which data flow transformation should you use?
B. Source Assistant
C. Destination Assistant
D. Script Component
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