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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 have a Microsoft SQL Server Analysis Services (SSAS) instance that is configured to use multidimensional mode. You create the following cube:
You need to create a new dimension that allows users to list shipments by the country where the product is shipped. Which relationship type should you use between the Shipment table and the new dimension?
A. no relationship
F. data mining
Many to Many Dimension Relationships.
In most dimensions, each fact joins to one and only one dimension member, and a single dimension member can be associated with multiple facts. In relational database terminology, this is referred to as a one-to-many relationship. However, it is frequently useful to join a single fact to multiple dimension members. For example, a bank customer might have multiple accounts (checking, saving, credit card, and investment accounts), and an account can also have joint or multiple owners. The Customer dimension constructed from such relationships would then have multiple members that relate to a single account transaction.
You are deploying a multidimensional Microsoft SQL Server Analysis Services (SSAS) project. You add two new role-playing dimensions named Picker and Salesperson to the cube. Both of the cube dimensions are based upon the underlying dimension named Employee in the data source view. Users report that they are unable to differentiate the Salesperson attributes from the Picker attributes. You need to ensure that the Salesperson and Picker attributes in each dimension use unique names. In the table below, identify an option that you would use as part of the process to alter the names of the attributes for each of the dimensions. NOTE: Make only one selection in each column.
A named query is a SQL expression represented as a table. In a named query, you can specify an SQL expression to select rows and columns returned from one or more tables in one or more data sources. A named query is like any other table in a data source view (DSV) with rows and relationships, except that the named query is based on an expression. A named query lets you extend the relational schema of existing tables in DSV without modifying the underlying data source.
You are building a Microsoft SQL Server Analysis Services multidimensional model over a SQL Server database. In a cube named OrderAnalysis, there is a standard cube dimension named Stock Item. This dimension has the following attributes:
– Users report that the attributes Stock Item Key and Photo are distracting and are not providing any value.
– They have asked for the attributes to be removed. However, these attributes are needed by other cubes.
You need to hide the specified attributes from the end users of the OrderAnalysis cube. You do not want to change the structure of the dimension. Which change should you make to the properties for the Stock Item Key and Photo attributes?
A. Set the AttributeHierarchyVisible property to False.
B. Set the AttributeHierarchyEnabledproperty to False.
C. Set the AttributeVisibility property to Hidden.
D. Set the Usage property to Regular.
E. Set the AttributeHierarchyDisplayFolder property to Hidden.
The value of the AttributeHierarchyEnabled property determines whether an attribute hierarchy is created. If this property is set to False, the attribute hierarchy is not created and the attribute cannot be used as a level in a user hierarchy; the attribute hierarchy exists as a member property only. However, a disabled attribute hierarchy can still be used to order the members of another attribute. If the value of the AttributeHierarchyEnabled property is set to True, the value of the AttributeHierarchyVisible property determines whether the attribute hierarchy is visible independent of its use in a user-defined hierarchy.
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