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Question 1:

You are designing a data warehouse for a software distribution business that stores sales by software title. It stores sales targets by software category. Software titles are classified into subcategories and categories. Each software title is included in only a single software 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 software title factTarget, used to record the monthly sales targets by software category

Reports must be developed against the warehouse that reports sales by software title, category and subcategory, and sales targets.

You need to design the software title dimension. The solution should use as few tables as possible while supporting all the requirements.

What should you do?

A. Create three software tables, dimSoftware, dimSoftwareCategory, and dimSoftwareSubcategory and a fourth bridge table that joins software titles to their appropriate category and subcategory table records with foreign key constraints. Direct the cube developer to use key granularity attributes.

B. Create three software tables, dimSoftware, dimSoftwareCategory, and dimSoftwareSubcategory. Connect factSales to all three tables and connect factTarget to dimSoftwareCategory with foreign key constraints. Direct the cube developer to use key granularity attributes.

C. Create one table, dimSoftware, which contains Software Detail, Category, and Subcategory columns. Connect factSales to dimSoftware with a foreign key constraint. Direct the cube developer to use a non-key granularity attribute for factTarget.

D. Create two tables, dimSoftware and dimSoftwareCategory. Connect factSales to dimSoftware and factTarget to dimSoftwareCategory with foreign key constraints. Direct the cube developer to use key granularity attributes.

Correct Answer: C


Question 2:

You are designing a data warehouse for a fresh food distribution business that stores sales 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.

Correct Answer: B


Question 3:

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 Windows Azure SQL Database. 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?

A. Multicast

B. Conditional Split

C. Script Task

D. Data Conversion

Correct Answer: B

Explanation: We use Conditional Split to split the source data into separate processing streams.

A Script Component (Script Component is the answer to another version of this question) could be used but this is not the same as a Script Task.


Question 4:

You are completing the installation of the Data Quality Server component of SQL Server Data Quality Services (DQS).

You need to complete the post-installation configuration.

What should you do?

A. Run the Data Quality Server Installer.

B. Install the data providers that are used for data refresh.

C. Run the dbimpexp.exe command.

D. Install the Analysis Services OLE DB Provider.

Correct Answer: A


Question 5:

Note: This 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 questions in this series.

Information and details provided in a question apply only to that question.

You are developing a Microsoft SQL Server Integration Services (SSIS) package.

You need to ensure that the packa

ge records the current Log Sequence Number (LSN) in the source database before the package begins reading source tables.

Which SSIS Toolbox item should you use?

A. CDC Control task

B. CDC Splitter

C. Union All

D. XML task

E. Fuzzy Grouping

F. Merge

G. Merge Join

Correct Answer: E


Latest 70-767 Dumps70-767 VCE Dumps70-767 Practice Test

Question 6:

Note: This 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 questions in this series.

Information and details provided in a question apply only to that question.

You are developing a Microsoft SQL Server Integration Services (SSIS) package.

You need to use XPath to extract information from documents.

Which SSIS Toolbox item should you use?

A. CDC Control task

B. CDC Splitter

C. Union All

D. XML task

E. Fuzzy Grouping

F. Merge

G. Merge Join

Correct Answer: B


Question 7:

You are developing a SQL Server Integration Services (SSIS) package that imports unsorted data into a data warehouse hosted on SQL Azure. You have the following requirements:

A destination table must contain all of the data in two source tables.

Duplicate records must be inserted into the destination table.

You need to develop a data flow that imports the data while meeting the requirements.

How should you develop the data flow? (To answer, drag the appropriate transformation from the list of transformations to the correct location in the answer area.)

Select and Place:

Correct Answer:


Question 8:

You are developing a SQL Server Integration Services (SSIS) package that is ready for deployment to a production server. The package contains sensitive information secured by using the EncryptSensitiveWithUserKey package protection

level.

You are preparing the package for deployment by the production operations team.

You need to ensure that the production operations team can open and execute the package without re-entering the sensitive information.

Which three steps 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.)

Select and Place:

Correct Answer:


Question 9:

You have a Microsoft SQL Server Integration Services (SSIS) package that contains a Data Flow task as shown in the Data Flow exhibit. (Click the Exhibit button.)

You install Data Quality Services (DQS) on the same server that hosts SSIS and deploy a knowledge base to manage customer email addresses. You add a DQS Cleansing transform to the Data Flow as shown in the Cleansing exhibit. (Click the Exhibit button.)

You create a Conditional Split transform as shown in the Splitter exhibit. (Click the Exhibit button.)

You need to split the output of the DQS Cleansing task to obtain only Correct values from the EmailAddress column. For each of the following statements, select Yes if the statement is true. Otherwise, select No.

Hot Area:

Correct Answer:

The DQS Cleansing component takes input records, sends them to a DQS server, and gets them back corrected. The component can output not only the corrected data, but also additional columns that may be useful for you. For example the status columns. There is one status column for each mapped field, and another one that aggregated the status for the whole record. This record status column can be very useful in some scenarios, especially when records are further

processed in different ways depending on their status.

Is such cases, it is recommended to use a Conditional Split component below the DQS Cleansing component, and configure it to split the records to groups based on the record status (or based on other columns such as specific field status).

References: https://blogs.msdn.microsoft.com/dqs/2011/07/18/using-the-ssis-dqscleansing-component/


Question 10:

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:

Implement table partitioning to improve the manageability of the data warehouse and to avoid the need to repopulate all transactional data each night. Use a partitioning strategy that is as granular as possible.

Partition the Fact.Order table and retain a total of seven years of data.

Partition the Fact.Ticket table and retain seven years of data. At the end of each month, the partition structure must apply a sliding window strategy to ensure that a new partition is available for the upcoming month, and that the oldest

month of data is archived and removed.

Optimize data loading for the Dimension.SalesTerritory, Dimension.Customer, and Dimension.Date tables.

Incrementally load all tables in the database and ensure that all incremental changes are processed.

Maximize the performance during the data loading process for the Fact.Order partition.

Ensure that historical data remains online and available for querying.

Reduce ongoing storage costs while maintaining query performance for current data.

You are not permitted to make changes to the client applications.

You need to optimize data loading for the Dimension.Customer table.

Which three Transact-SQL segments should you use to develop the solution? To answer, move the appropriate Transact-SQL segments from the list of Transact-SQL segments to the answer area and arrange them in the correct order.

NOTE: You will not need all of the Transact-SQL segments

Select and Place:

Correct Answer:

Step 1: USE DB1

From Scenario: 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.

Step 2: EXEC sys.sp_cdc_enable_db

Before you can enable a table for change data capture, the database must be enabled. To enable the database, use the sys.sp_cdc_enable_db stored procedure.

sys.sp_cdc_enable_db has no parameters.

Step 3: EXEC sys.sp_cdc_enable_table

@source schema = N \’schema\’ etc.

Sys.sp_cdc_enable_table enables change data capture for the specified source table in the current database.

Partial syntax:

sys.sp_cdc_enable_table

[ @source_schema = ] \’source_schema\’,

[ @source_name = ] \’source_name\’ , [,[ @capture_instance = ] \’capture_instance\’ ]

[,[ @supports_net_changes = ] supports_net_changes ]

Etc.

References:

https://docs.microsoft.com/en-us/sql/relational-databases/system-storedprocedures/sys-sp-cdc-enable-table-transact-sql

https://docs.microsoft.com/en-us/sql/relational-databases/system-stored-procedures/syssp-cdc-enable-db-transact-sql


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