How to Build a Cube and Write MDX with OLAP Using 2014 AdventureWork

Data Warehouse

Sunnie Chung

Project Description

Buding a Business Analytic Data Mining Model using Microsoft BI Data Mining Tool and Data Warehouse

and OLAP Cubes.

Preparation of Project

1.Installing the SSDT BI for Visual Studio 2013

Tutorial: https://www.youtube.com/watch?v=C5GpYd0y4wo

After successful installations, I start a project by following steps:

1) Open Visual Studio

2) File -> New Project

3) You should see following BI add-ons which lets you create Data mining projects.

a. Analysis Service

b. Integration Service

c. Reporting Service

4) Create an Analysis Services project and name it, then click ok.

2. Installing Adventure Works 2014 database for SQL Server 2014

Design a Cube with Dimensions

1.Building a Data Source

In The solution explorer, right click on Data Sources and click New Data Source and click New Data

Source. This will bring up the Data Source Wizard, which will walk you through the creation process. The

database I used is AdventureWorksDW2014.

Choose Inherit and then click next

Enter data source name ”Lab3” and then click finish.

2.Building a Data Source View

Right-click Data Source Views and choose New Data Source View. Make sure the Lab3 data source is

selected and then click Next.

On Select Table and Views , I choose these dimensions and fact table :

DimCustomer, DimGeography, DimProduct, DimDate , DimSalesTerritory and FactInternetSales

Name the view : Internet Sales

The star schema of Internet Sales data.

3.Creating an Analysis Services Cube

Right-click Cubes in the Solution Explorer and select New Cube to bring up the Cube Wizard and then

click next. On the Select Creation Method screen, make sure Use Existing Tables is selected, and click

Next.

Choose FactInternetSale as measure group and select measures that you want to include into cube.

After that, based on available tables, select new dimensions to be created.

Enter name and finished.

4. Deploying the cube

Right click project name and then click Deploy.

I got the first Error due to the connection cannot be made

Because the start mode of SQL server Analysis Service is manual, the state of it is default stopped. So I

open sql Server Configuration Manager to change the state of SQL server Analysis Service to Running.

Repeat deploying process, I got another error: Contains an Impersonation Mode that is not supported

for processing operations.

Fix: Double click on ds file (in this case which is Lab3.ds) to open Data source designer. In the

impersonation tab, select windows user name and password and enter the windows login user id and

password and now process the cube.

Deploying project works now.

Right click Internet Sales.cube and hit process. After deployment completed successfully, click run.

We can see cube deployed successfully.

5. Editing Dimensions Individually

Right click dimensions name and click New Attribute from Column or drag the attribute from the pane of

data source view to attributes pane. By using this way, I edit all dimensions individually.

Deploying the cube again

Writing MDX queries to retrieve data

1. Open SQL Server 2014 and select Analysis Services as server type. After connecting, we can find the

cube Internet Sales has already in SQL server.

2. Right click project name and select New Query and then click MDX.

We can find all the dimensions and their attributes in the panes.

Q1: Predict which cities we need more bikes supply to in 2014.

Find out how many bikes have been sold in particular city in 2013. The following statement find top 20

cities which has best order quantity.

select[measures].[order quantity] on 0, TopCount

({[dim geography].[city].members

*[order date].[calendar year].[2013]} ,20

,[measures].[order quantity]

) ON 1 from [Internet Sales]

Top 5 cities in order quantity:

Drill down on each quarter

Using following statement to see the purchase of bikes in each quarter in year 2013.

select ([order date].[calendar quarter].members)on columns,

filter([Dim geography].[city].members,

[order date].[calendar year].[2013]) on rows

from[internet sales] where([measures].[sales amount])

Save the table into excel and sorted in descending order of their total sales amount of year 2013

I select top 10 sale amounts cities and plot a quarter graph. We can see during quarter 4th the sales of

bikes usually get the peak value. We also can notice that some cities (e.g. Goulburn) have downward

tendency.

0

50000

100000

150000

200000

250000

300000

quarter1 quarter2 quarter3 quarter4

London

Paris

Wollongong

Warrnambool

Bendigo

Goulburn

Bellflower

Brisbane

Townsville

Geelong