2.2 check Multidimensional Dataset and latitude attributes

In the cube designer, you can view and edit attributes of a cube. The designer contains the following tabs that display different views of a cube.

Multi-dimensional dataset Structure

You can use this tab to modify the cube architecture.

Dimension usage

You can use this tab to define the relationship between a dimension and a measurement value group, and the granularity of each dimension in each measurement value group. If you use multiple fact tables, you may need to identify whether the measurement value is not applicable to one or more dimensions. Each cell represents the potential relationship between the intersection measurement value group and dimension.

Computing

On this tab, you can view the calculations defined for the multi-dimensional dataset, define new computations for the entire multi-dimensional dataset or sub-multi-dimensional dataset, re-sort the existing computation, and debug the computation step by step using the breakpoint. Using computation (such as profit calculation), you can define new members and measurement values based on existing values, and you can also define a nameset.

KPI

You can use this tab to create, edit, and modify key performance metrics (KPIs) in a cube ). By using KPIs, developers can quickly determine useful information about a specific value, such as whether the defined value exceeds the target or fails to reach the target, or whether the defined value trend is getting better or worse.

Operation

You can use this tab to create or modify drill-through, report, and other operations for the selected cube. Operation can be applied to the clientProgramProvides contextual information, commands, and reports that end users can access.

Partition

You can use this tab to create and manage partitions of a cube. Through partitioning, you can use different attributes (such as aggregate definitions) to store different parts of a cube in different locations.

Perspective

Use this tab to create and manage pivoting in a cube. Pivot is a defined subset of a multi-dimensional dataset. It is used to reduce the subjective complexity of a multi-dimensional dataset for business users.

Translation

You can use this tab to create and manage the translation names (such as month names or product names) of cube objects ).

Browser

Use this tab to view data in a cube.

Check the attributes of a cube and dimension in the cube designer.

2. in the cube designer, on the "Multidimensional Dataset structure" tab, In the "measurement value" pane, expand the Internet sales measurement group.

   the metric value defined by the Internet sales metric group is displayed. You can drag these measurements to the desired order to change the order of these measurements. The order of metric values will affect how some client applications sort these metric values. The measurement value group is named Internet sales because the friendly name of the basic fact data table in the data source view is internetsales. Note that a space is automatically added before the uppercase letter "S" to add user-friendly features for the name. A measurement value group and each measurement value have attributes. You can edit these attributes in the Properties window. In Lesson 3rd, you will learn how to modify the attributes of these metric values.

   the measurement group and measurement value in the "Metric value" pane of the cube designer are displayed.

4. In the cube designer"Multidimensional Dataset structure"Tab"Dimension"In the pane, check the dimension of the Multidimensional Dataset in the analysis services tutorial cube.

   Note: although only three dimensions are created at the database level (as shown in solution Resource Manager), there are five dimensions in the analysis services tutorial cube. The multi-dimensional dataset contains more dimensions than the database because it is based on different time-related fact data in the fact data table, the "time" database dimension is used as the basis for three time-related individual cube dimensions. These time-related dimensions are also called "role-playing dimensions". With three time-related Multidimensional Dataset dimensions, you can organize dimensions in a Multidimensional Dataset according to the following three separate fact data related to sales of each product: product order date, fulfillment order expiration date, and order delivery date. By repeatedly applying a single database dimension to multiple cube dimensions, analysis services simplifies dimension management, reduces disk space usage, and reduces the overall processing time.

5. In"Multidimensional Dataset structure"Tab"Dimension"In the pane, expand"Customer"And then click"Edit 'customer '".

   the customer dimension is displayed in the dimension designer. (Note that the data source view designer and cube designer are still on .) The dimension designer has the following tabs: "Dimension Structure" , "Translation" , and "Browser" . Note: The dimension structure tab contains the following three tabs: "attribute" , "hierarchy and level" , and "Data Source view" . The "properties" pane displays the properties designed by the cube wizard, the hierarchy and level pane displays the user hierarchy defined by the cube wizard. The "Data Source view" pane displays tables in the data source view. columns are used as attributes in this dimension.

   In the dimension designer's"Dimension Structure"Tab to add, delete, and edit hierarchies, levels, and attributes. In Lesson 3rd, you will learn how to execute these tasks. For more information, see: , ,

   Displays"Dimension Structure"Tab.

7. On the Design Environment tab, or in Solution Explorer, right-click the Analysis Services tutorial cube in the cube node, and then click"View designer"To switch to the Cube designer.

9. In the cube designer, click"Dimension usage"Tab.

   In the analysis services tutorial Multidimensional Dataset view, you can see the Multidimensional Dataset dimensions used by the Internet sales measurement value group. If a cube contains multiple measurement groups, the dimension of the cube may be used only for some measurement groups, but not for other measurement groups. In addition, you can define the relationship types between each dimension and each measurement value group using this dimension. In Lesson 4th and lesson 5th, we will learn more about the usage of dimensions and the relationship between dimensions and measurement value groups.

   Shows"Dimension usage"Tab.

11. At the intersection of the Internet sales measurement value group and customer dimension, click"Customer"Next"Customer"Field, and then click the ellipsis (...).

    In this case"Define link"Dialog box. In this dialog box, you can define custom dimension attributes in a specific measurement value group. By default, dimensions have the same behavior in each measurement value group. However, they may have different behaviors in different measurement value groups. Note that the relationship between the "customer" dimension and the "Internet sales" Metric value is a general relationship, that is, the dimcustomer dimension table is directly connected to the factinternetsales metric value group table. Note that the granularity of this dimension is at the lowest level (that is, the "customer" level), but different levels of granularity can be defined. In Lesson 5th, we will learn how to define custom granularity levels.

    Shown"Define link"Dialog box.

13. click "advanced" .

    the "bind measurement group" dialog box is displayed, in this dialog box, you can modify the binding of each attribute and define the null value processing settings. Attribute binding can specify the columns in the basic dimension table to which the attribute is bound. By default, this setting inherits from the dimension. This setting is rarely changed at the measurement value group level. By setting null values, you can define how Analysis Services processes null values at the measurement value group level during processing. These settings will overwrite any dimension settings. In Lesson 4th, we will learn how to define null value processing settings at the dimension level. For more information, see:

    the "bind measurement group" dialog box is displayed.

15. Click"Cancel", Click"Cancel", Returns the cube designer.

    In this task, we will not check"Computing","KPI","Operation","Perspective"And"Translation"Tab, because related objects are not defined in the Tutorial Project. These tabs are detailed in Lesson 6th, 7, 8, and 9.

16. Click"Partition"Tab.

    The multi-dimensional dataset wizard can use a multi-dimensional Online Analytical Processing (molap) storage mode without aggregation to define a single partition for a multi-dimensional dataset. With molap, all leaf-level data and all aggregation are stored in a multi-dimensional data set to maximize performance. Aggregation is a pre-computed data summary. Aggregation can prepare answers before the question is raised, which can shorten the query response time. Aggregation is usually defined before the Analysis Services Project is finally deployed to the production server. Aggregation is not defined during development. Note that "Partition" You can define other partitions, storage settings, and write-back settings on the tab. This tutorial does not include defining aggregation and partitioning. For more information, see , , ,

    Shows"Partition"Tab.

18. click the browser tab.

    Note: you cannot browse a cube because it is not deployed in an analysis services instance. In this case, the Multidimensional Dataset in the analysis services Tutorial Project is only a Multidimensional Dataset definition that can be deployed to any analysis services instance. When you deploy and process multi-dimensional data sets, you will create defined objects in the analysis services instance, and then fill these objects with the data of the basic data source.

    the "Browser" tab in the cube designer is displayed.

20. In Solution Explorer, right-click"Multi-dimensional dataset"NodeAnalysis Services tutorialAnd then click"ViewCode".

    On the Analysis Services tutorial. cube [XML] tab, the XML code of the Analysis Services tutorial cube is displayed. This is the actual code used to create a cube in an analysis services instance during deployment. For more information, see:

    Shows the XML code of the cube.

22. Close the XML Code tab.

you have checked the initial analysis services tutorial multi-dimensional dataset and can deploy it to the Analysis Services instance. Although many multi-dimensional datasets and dimension metadata can be edited without project deployment, you can view the actual data in the multi-dimensional datasets and dimension designer to help you during the development process. For example, you must deploy and process a multi-dimensional dataset to view the order of dimension members.