You are implementing a SQL Server Integration Services (SSIS) package that loads data hosted in a SQL Azure database into a data warehouse. The source system contains redundant or inconsistent data. When the package finds invalid data, the row containing the invalid data must be omitted but it must also be written to a text file for further analysis. You need to establish the best technique to log these invalid rows while keeping the amount of development effort to a minimum. What should you do?
A. Add an OnError event handler to the SSIS project.
B. Use an msi file to deploy the package on the server.
C. Open a command prompt and run the gacutil command.
D. Open a command prompt and run the dtutil /copy command.
E. Open a command prompt and run the dtexec /rep /conn command.
F. Open a command prompt and run the dtexec /dumperror /conn command.
G. Open a command prompt and execute the package by using the SQL Log provider and running
the dtexecui.exe utility.
H. Create a reusable custom logging component and use it in the SSIS project.
I. Configure the SSIS solution to use the Project Deployment Model.
J. Configure the output of a component in the package data flow to use a data tap.
K. Run the dtutil command to deploy the package to the SSIS catalog and store the configuration in
To ease the debugging of packages, you standardize the SQL Server Integration Services (SSIS) package logging methodology. The methodology has the following requirements:
* Centralized logging in SQL Server
* Simple deployment
* Availability of log information through reports or T-SQL ?Automatic purge of older log entries
* Configurable log details
You need to configure a logging methodology that meets the requirements while minimizing the amount of deployment and development effort. What should you do?
A. Use the gacutil command.
B. Use the dtutil /copy command.
C. Use the Project Deployment Wizard.
D. Create an OnError event handler.
E. Create a reusable custom logging component.
F. Run the package by using the dtexec /rep /conn command.
G. Run the package by using the dtexec /dumperror /conn command.
H. Run the package by using the dtexecui.exe utility and the SQL Log provider.
I. Add a data tap on the output of a component in the package data flow.
J. Deploy the package by using an msi file.
K. Deploy the package to the Integration Services catalog by using dtutil and use SQL Server to
store the configuration.
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 correct answer presents a complete solution. Choose all that apply.)
B. Merge Join
C. Term Extraction
D. union All
You are designing a SQL Server Integration Services (SSIS) package that uses the Fuzzy Lookup transformation. The reference data to be used in the transformation does not change. You need to reuse the Fuzzy Lookup match index to increase performance and reduce maintenance. What should you do?
A. Select the GenerateAndPersistNewIndex option in the Fuzzy Lookup Transformation Editor.
B. Select the GenerateNewIndex option in the Fuzzy Lookup Transformation Editor.
C. Select the DropExistingMatchlndex option in the Fuzzy Lookup Transformation Editor.
D. Execute the sp_FuzzyLookupTableMaintenanceUninstall stored procedure
E. Execute the sp_FuzzyLookupTableMaintenanceInvoke stored procedure.
You are developing a SQL Server Integration Services (SSIS) package. You need to design a package to change a variable value during package execution by using the least amount of development effort.
What should you use?
A. Expression task
B. Script task
C. Execute SQL task
D. Execute Process task
E. Term Extraction transformation
You are creating a SQL Server Master Data Services (MDS) model for a company. The source data for the company is stored in a single table that contains the manager-to-subordinate relationships. You need to create a hierarchy representing the organizational structure of the company. Which hierarchy type should you use?
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 Configuration component in the Data Quality Client.
B. Install ADOMD.NET.
C. Run the Data Quality Server Installer.
D. Make the data available for DQS operations.
You are the data steward for a Business Intelligence project. You must identify duplicate rows stored in a SQL Server table and output discoveries to a CSV file. A Data Quality Services (DQS) knowledge base has been created to support this project. You need to produce the CSV file with the least amount of development effort. What should you do?
A. Create an Integration Services package and use a Data Profiling transform.
B. Create a custom .NET application based on the Knowledgebase class.
C. Create a data quality project.
D. Create a CLR stored procedure based on the Knowledgebase class.
E. Create a Master Data Services (MDS) business rule.
You are implementing the indexing strategy for a fact table in a data warehouse. The fact table is named Quotes. The table has no indexes and consists of seven columns:
Each of the following queries must be able to use a columnstore index:
SELECT AVG ([Close]) AS [AverageClose] FROM Quotes WHERE [QuoteDate] BETWEEN ‘20100101’ AND ‘20101231’.
SELECT AVG([High] – [Low]) AS [AverageRange] FROM Quotes WHERE [QuoteDate] BETWEEN ‘20100101’ AND
SELECT SUM([Volume]) AS [SumVolume] FROM Quotes WHERE [QuoteDate] BETWEEN ‘20100101’ AND ‘20101231’.
You need to ensure that the indexing strategy meets the requirements. The strategy must also minimize the number and size of the indexes. What should you do?
A. Create one columnstore index that contains [ID], [Close], [High], [Low], [Volume], and [QuoteDate].
B. Create three coiumnstore indexes:
One containing [QuoteDate] and [Close]
One containing [QuoteDate], [High], and [Low]
One containing [QuoteDate] and [Volume]
C. Create one columnstore index that contains [QuoteDate], [Close], [High], [Low], and [Volume].
D. Create two columnstore indexes:
One containing [ID], [QuoteDate], [Volume], and [Close] One containing [ID], [QuoteDate], [High], and [Low]
You are designing a data warehouse with two fact tables. The first table contains sales per month and the second table contains orders per day. Referential integrity must be enforced declaratively. You need to design a solution that can join a single time dimension to both fact tables. What should you do?
A. Join the two fact tables.
B. Merge the fact tables.
C. Create a time dimension that can join to both fact tables at their respective granularity.
D. Create a surrogate key for the time dimension.
http://msdn.microsoft.com/en-us/library/ms174884.aspx http://decipherinfosys.wordpress.com/2007/02/01/surrogate-keys-vs-natural-keys-for-primary-key/ http://www.agiledata.org/essays/keys.html
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