Data mining in Sql Server 2008 & Visual Studio
May 25, 2011 Leave a comment
Creating a Project in the Business Intelligence Development Studio
Follow these steps to create a new project. To start BIDS, click the Start button and go to All Programs->Microsoft SQL Server 2008->SQL Server Business Intelligence Development Studio. In BIDS, select File New Project. You will see the Business Intelligence Projects template. Click the Analysis Services Project template. Type “AnalysisServices2008Tutorial” as the project name and select the directory in which you want to create this project. Click OK to create the project.
The Solution Explorer Pane
The Solution Explorer contains the following:
1) Data source objects: They contain details of a connection to a data source, which include server name, catalog or database name, and login credentials. You establish connections to relational servers by creating a data source for each one.
2) Data Source Views: When working with a large operational data store you don’t always want to see all the tables in the database. With Data Source Views (DSVs), you can limit the number of visible tables by including only the tables that are relevant to your analysis.
3) Cubes: A collection of measure groups (from the fact tables) and a collection of dimensions form a cube. Each measure group is composed of a set of measures. Cubes can have more than three dimensions and not necessarily the three – dimensional objects as their name suggests.
4) Dimensions: They are the set of tables that are used for building the cube. Attributes that are needed for the analysis task are selected from each table.
5) Mining Structures: Data mining is the process of analyzing raw data using algorithms that help discover interesting patterns not typically found by ad – hoc analysis. Mining Structures are objects that hold information about a data set. A collection of mining models form a mining structure. Each mining model is built using a specific data mining algorithm and can be used for analyzing patterns in existing data or predicting new data values.
The Properties Pane
If you click an object in the Solution Explorer, the properties for that object appear in the Properties pane. Items that cannot be edited are grayed out. If you click a particular property, the description of that property appears in the Description pane at the bottom of the Properties pane.
Data mining in sql server 2008
The data mining process is regarded as a series of steps to be followed which include the following:
1) Creating a Data Source:
Cubes and dimensions of an Analysis Services database must retrieve their data values from tables in a relational data store. This data store, typically part of a data warehouse, must be defined as a data source.
To create a data source, follow these steps:
a) Select the Data Sources folder in the Solution Explorer.
b) Right – click the Data Sources folder and click New Data Source. This launches the Data Source Wizard.
c) In the data source wizard you will provide the connection information about the relational data source that contains the “Adventure Works DW 2008” database. Click the New button under Data Connection Properties to specify the connection details. You will enter here the server name, the database name, and choose one of the two authentication modes either sql server authentication or windows authentication.
d) In the Impersonation Information page you need to specify the impersonation details that Analysis Services will use to connect to the relational data source. There are four options. You can provide a domain username and password to impersonate or select the Analysis Service instance’s service account for connection. The option Use the credentials of the current user is primarily used for data mining where you retrieve data from the relational server for prediction. If you use the Inherit option, Analysis Services uses the impersonation information specified for the database.
e) On the final page, the Data Source Wizard chooses the relational database name you have selected as the name for the data source object you are creating. You can choose the default name specified or specify a new name here.
2) Creating a Data Source View ( DSV )
The Adventure Works DW database contains 25 tables. The cube you build in this chapter uses 10 tables. Data Source Views give you a logical view of the tables that will be used within your OLAP database.
To create a Data Source View, follow these steps:
a) Select the Data Source Views folder in the Solution Explorer.
b) Right – click Data Source Views and select New Data Source View. This launches the Data Source View Wizard.
c) In the data source view wizard you can select the tables and views that are needed for the Analysis Services database you are creating. Click the > button
so that the tables move to the Included Objects list. We will include in the data source view here the following set of tables:
FactInternetSales, FactResellerSales, DimProduct, DimReseller, DimPromotion, DimCurrency, DimEmployee, DimSalesTerritory, DimTime, DimCustomer, Dim Geography.
d) At the final page of the DSV Wizard you can specify your own name for the DSV object or use the default name. Specify the “Adventure Works DW” for the DSV Name in the wizard and click Finish.
If you open the data source view in the solution explorer the data source view editor opens which contains three main areas: Diagram Organizer, the Tables view, and the Diagram view. In the diagram view you can see a diagram of all the added tables with their relationships among each other. In the tables view you can see all the tables that are contained in this data source view. In the diagram organizer, you can right click in the pane here to create a new diagram and drag and drop the tables that u wish to add, or simply add any table u want then right click on it and choose add related tables, this will add all the related tables to the given chosen table. In order to add a new field to a given table, you simply right click on the table in the diagram view and choose add named reference, a dialog will appear where you can enter the name of the new field and the formula upon which it is derived. For example, to add a new field named FullName to the table employee, you write the following formula: FirstName + ‘ ‘ + MiddleName + ‘ ‘ + LastName.
There are different layouts in the data source view. You can switch between rectangular layout and diagonal layout in the DSV by right – clicking in the DSV Designer and selecting the layout type of your choice.
To see a sample of the data specified by your DSV, right – click a table in the DSV Designer and select Explore Data. The data presented is only a subset of the underlying table data. By default the first 5,000 rows are retrieved and shown within this window. You can change the number of rows retrieved by clicking the Sampling Options button. Clicking the Sampling Options button launches the Data Exploration Options dialog where you can change the sampling method, sample count, and number of states per chart, which is used for displaying data in the chart format.
When you click the Pivot Table tab you get an additional window called PivotTable Field List that shows all the columns of the table. You can drag and drop these columns inside the pivot table in the row, column, details, or filter areas. The values in the row and column provide you with an intersection point for which the detailed data is shown.
3) Creating New Dimensions
Dimensions help you define the structure of your cube so as to facilitate effective data analysis. Specifically, dimensions provide you with the capability of slicing data within a cube, and these dimensions can be built from one or more dimension tables.
a) Create the DimGeography dimension:
Launch the Dimension Wizard by right – clicking Dimensions in the Solution Explorer and selecting New Dimension.
In the Select Creation Method screen select the “Use an existing table” option and click next.
In the Specify Source Information page, you need to select the DSV for creating the dimension, select the main table from which the dimension is to be designed, specify the key columns for the dimension, and optionally specify a name column for the dimension key value. By default, the first DSV in your project is selected. Because the current project has only one DSV (the Adventure WorksDW DSV), it is selected. Select the DimGeography table from the Main table drop – down list.
Click the Next button to proceed to the next step in the Dimension Wizard.
The Dimension Wizard now analyzes the DSV to detect any outward – facing relationships from the DimGeography table. An outward – facing relationship is a relationship between the DimGeography table and another table, such that a column in the DimGeography table is a foreign key related to another table. The Select Related Tables screen shows that the wizard detected an outward relationship between the DimGeography table and the DimSalesTerritory table. In this example you will be modeling the DimGeography table as a star schema table instead of snowflake schema. Deselect the DimSalesTerritory table and click next.
The Select Dimension Attributes screen of the Dimension Wizard displays the columns of the main table that have been selected for the dimension you’re creating.
Select all the attributes of the DimGeography table (all the attributes in the screen), leave their Attribute Type as Regular, allow them to be browsed, and click next.
The final screen of the Dimension Wizard shows the attributes that will be created for the dimension based on your choices in the wizard. Click the Finish button.
Open the DimGeography dimension by double clicking on it in the solution explorer. In the Dimension structure tab you can see all the table attributes that have been added to this dimension. In the hierarchies’ pane, drag and drop the English country region name attribute followed by the State Province Name followed by the city and then the postal code. Then you have to build the relationships among these attributes in the hierarchy by clicking on the attribute relationships tab, and then dragging the postal code attribute towards the city, this means that the postal code value determines
the city. Drag the city towards the state. Drag the state towards the country. This will build the functional dependencies among the attributes in the hierarchy. Then you have to ensure that the city value is unique in determining the state name value by setting the key columns property of the city attribute to both the state province code and city, and setting its name columns to the city attribute. Similarly set the key columns of the postal code attribute to the postal code, the city, and the state province code attributes, and set its name columns to the postal code.
Deploy the project, by right clicking the project name and choosing deploy. After a successful deployment, you can browse the dimension by selecting the browse tab, where you can see all the data of the dimgeography table arranged according to their hierarchical levels.
b) Create the DimTime dimension
Launch the Dimension Wizard by right – clicking Dimensions in the Solution Explorer and selecting New Dimension. When the welcome screen of the Dimension Wizard opens up, click next.
In the Select Creation Method page of the wizard, select the “Use an existing table” option and click next.
In the Specify Source Information page, select DimTime as the main table from which the dimension is to be designed and click next.
In the Select Dimension Attributes page, in addition to the Date Key attribute, enable the checkboxes for the following attributes: Calendar Year, Calendar Semester, Calendar Quarter, English Month Name, and Day Number of Month.
Set the Attribute Type for the “Calendar Year” attribute to Date Calendar Year.
Set the Attribute Type for the “Calendar Semester” attribute to Date Calendar Half Year.
Set the Attribute Type for the “Calendar Quarter” attribute to Date Calendar Quarter.
Set the Attribute Type for the “English Month Name” attribute to Date Calendar Month.
Set the Attribute Type for the “Day Number of Month” attribute to Date Calendar Day of Month.
Create a multilevel hierarchy Calendar Date with the levels Calendar year, Calendar Semester, Calendar Quarter, Month (rename English Month Name), and Day (rename Day Number Of Month).
Save the project and deploy it to the analysis services instance.
Switch to the Browser pane of the DimTime dimension, where you can see that the date hierarchy is arranged according to the hierarchy that we defined above.
c) Create the DimEmployee dimension
Launch the Dimension Wizard by right – clicking Dimensions in the Solution Explorer and selecting New Dimension. If the welcome screen of the Dimension Wizard opens up, click next.
Make sure the “Use an existing table” option is selected and click next.
In the Specify Source Information page, select DimEmployee as the main table from which the dimension is to be designed and click next.
On the Select Related Tables screen, uncheck the DimSalesTerritory table and click next.
In the Select Dimensions Attributes dialog, the Dimension Wizard has detected three columns of the DimEmployee table to be included as attributes. The Dimension Wizard will select columns if they are either the primary key of the table or a foreign key of the table or another table in the DSV. The attributes suggested by the Dimension Wizard in this example are the key attribute Employee Key, the parent – child attribute Parent Employee Key, and the Sales Territory Key, which is a foreign key column to the DimSalesTerritory table.
Select all the columns of the DimEmployee table as attributes and click next.
Double – click the DimEmployee dimension in the Solution Explorer to open the Dimension Designer.
Change the NameColumn property of the Key attribute Dim Employee to FullName and deploy the project to your Analysis Services instance.
When you browse the Parent – Child hierarchy, you will see the members of the hierarchy showing the full names of the employees.
4) Creating a Cube Using the Cube Wizard
Cubes are the principal objects of an OLAP database that help in data analysis. Cubes are multidimensional structures that are primarily composed of dimensions and facts. The data from a fact table that is stored within the cube for analysis are called measures.
To build a new cube, follow these steps:
a) Right – click the Cubes folder and select New Cube. Click next on the introduction page to proceed.
b) In the Select Creation Method page you have the option to build a cube from existing tables, create an empty cube, or create a cube based on a template and generate new tables in the data source. Choose to build the cube from the existing tables in the Adventure Works DW data source. Click Next to proceed to the next step in the Cube Wizard.
c) The next page of the Cube Wizard is the Measure Group Tables selection page. You now must select one or more tables that will serve as fact tables for your Measure Group. The Suggest button on this screen can be used to have the Cube Wizard scan the DSV to detect the fact tables in the DSV and
detect fact tables. Click the Suggest button to have the Cube Wizard automatically select potential Measure Group tables. The Cube Wizard now scans the DSV to detect the fact and dimension tables in the DSV, automatically selects the candidate tables. Any table that has an outgoing relationship is identified as a candidate fact table, whereas a table that has an incoming relationship is detected as a dimension table. Select both the FactResellerSales and the FactInternetSales as the fact tables. And then select the measures that you need to include from these fact tables for the analysis task.
d) In the Select Existing Dimensions page, the Cube Wizard displays a list of all existing dimensions defined in the project. Accept the selection of all the dimensions and click next.
e) The Cube Wizard asks you to select any new dimensions to be created from existing tables in the data source that are not already used for dimensions in the project. You can deselect dimensions that are not needed for your cube on this page. This illustration will use the Fact tables only as measure groups and not for dimensions. Deselect the Fact Reseller Sales and Fact Internet Sales dimensions on this page and click next.
f) In the final page of the Cube Wizard you can specify the name of the cube to be created and review the measure groups, measures, dimensions, attributes, and hierarchies. Use the default name Adventure Works DW suggested by the Cube Wizard and click Finish.
After creating the cube, the new dimensions are automatically created. But these dimensions will have only their primary and foreign keys selected. You have to open each created dimension and select the attributes that you need to add from each table.
g) Press F5 to deploy, build and process the cube. Deploying the cube means building the cube according to the structure that you have defined, while processing the cube means computing all the aggregation values for all the cells in the cube.
You can add a new calculated measure to the cube by Right – clicking in the Script Organizer pane of the Calculation Scripts tab and entering the formula for this new measure.
Now that the cube has been deployed, switch the BIDS Cube Designer view to the Browser page. In the Browser page you will see three panes: a Measure Group pane, a Filter pane, and a Data pane. Suppose you want to analyze the Internet sales of products based on the promotions offered to customers and the marital status of those customers. First you would need to drag and drop [DimPromotion].[English Promotion Type] from the Measure Group pane to the OWC rows area. Next, drag and drop [Dim Customer].[Marital Status] from the Measure Group pane to the OWC columns area. Finally, drag and drop the measure [Sales Amount] from the Fact Internet Sales measure group to the Drop Totals or Detail Fields Here area of the OWC pane.
You can also use MDX queries to query the cube. These MDX queries are similar to the sql server queries. Just as SQL (Structured Query Language) is a query language used to retrieve data from relational databases, MDX (Multi – Dimensional expressions) is a query language used to retrieve data from multidimensional databases.
The format of MDX query is shown below:
SELECT [< axis expression >, [< axis expression > …]]
FROM [< cube_expression >]
[WHERE [slicer expression]]
5) Creating a Mining Structure
Analysis Services 2008 provides nine data mining algorithms that can be utilized to solve various business problems. These algorithms can be broadly classified into five categories based on the nature of the business problem they can be applied to. They are:
4) Sequence analysis
We aim at grouping customers that undergo similar characteristics.
To create a relational mining model, follow the following steps:
a) Right – click the Mining Structures folder in the Solution Explorer and select New Mining Structure as to launch the Data Mining Wizard that helps you to create data mining structures and models. Click the Next button.
b) Select the “From existing cube” radio button and click next.
c) Select Microsoft Clustering and click next.
d) Choose the Customer table as the primary table and enter the following attributes as inputs for building clusters:
Age, Yearly Income, Number of cars owned, Number of Children at home and Occupation.
You will now see the clustering mining model represented as several nodes with lines between these nodes. By default the clustering mining model groups the customer into ten different clusters. The number of clusters generated can be changed from a property for the cluster mining model. Each cluster is shown as a node in the cluster viewer. Darker shading on the node indicates that the cluster favors a specific input column and vice versa. If there is a similarity between two clusters, it is indicated by a line connecting the two nodes. Similar to the shade of the color node, if the relationship is stronger between two nodes, it is indicated via a darker line. You can move the slider on the left of the cluster diagram from All Links to Strongest Links. As you do this you can see the weaker relationships between the clusters are not displayed. You can change the cluster name by right – clicking the cluster and selecting Rename. You can select desired input columns of the mining model from the Shading Variable drop –
down to see the effect of the column on the various clusters. When you choose a specific shading variable column you need to choose one of the states of the column to be used as the shading variable for the clusters.
The Cluster Profiles view shows the relationship between the mining columns of the model and the clusters in a matrix format. The intersection cell of a specific column and a cluster shows a histogram bar of the various values of the column that are part of the cluster. The size of each bar reflects the number of items used to train the model.
The cluster Characteristics tab shows the characteristics of a single cluster and how the various states of the input columns make up the cluster.
The Cluster Discrimination tab shows the characteristics of a Cluster in comparison with the characteristics of the complement of this Cluster.