IT462 Lab 2: Data warehousing and On-Line Analytic Processing (OLAP)
This lab should get you familiar with use of aggregation and visualization techniques to help you make decisions from your data.
The following tables should now be part of your database (primary keys are underlined, foreign keys are italic):
Users(UserID, Password, Type, CompanyNumber)
Products(BarCode, PName, Price)
Orders(OrderID, UserID, Year, Month, Day)
OrderDetails(OrderID, BarCode, Quantity)
PART 1:
Dimensional Modeling
We would like to have a data warehouse and use OLAP to answer questions like:
Use dimensional
modeling to design the structure of the data warehouse. The final result should
have a “star schema”.
Write the answers to the following questions
in yourlastname_Lab2.doc file.
PART 2:
Extract-Transform-Load (ETL)
Add
the CREATE TABLE statements to create the tables to yourlastname_Lab2.doc file.
INSERT INTO TableName(col1, col2, …)
SELECT col1, col2, … FROM …
Write the statements to populate the tables
into yourlastname_Lab2.doc file
PART 3: Analyze
the data
Part 3.1: Create a connection
We will need to connect to this wealth of data using an Open Database Connection (ODBC). On XP or Windows7, you find this set up under Control Panel->(System and Security) ->Administrative Tools->Data Sources (ODBC). Click on add, and find the SQL Server Native Client Driver, probably at the bottom of your list.


Name the new USER DSN connection mXXXXXX_wardroom where XXXXXX is your
alpha and configure the connection as shown in the screen shots below, using
cardhu.cs.usna.edu, your database, username and password. Change the default
database to be your own database (mXXXXXX instead of master). Leave all other options at their default
values and click “next” until you get a success message.




Open Excel
(Start->All Programs->Microsoft Office-> Excel) and save the file as
Yourlastname_Lab3.xls. We are going to
create a mechanism to aggregate this dataset and allow you to make some
intelligent decisions. Select Data->Get
External Data-From Other Sources ->From Microsoft Query.

Select the datasource
that you created, mXXXXXX_wardroom and provide a password to connect if asked.

Then select the
columns that you will need for your analysis (see below). In the original
tables, the following columns were of interest. You should select the corresponding
columns in the tables you designed in Part 1 and 2: Orders->Month,
OrderDetails->Quantity, Products->Price, PName and Users->
CompanyNumber. Don’t bother filtering or
sorting the data.

Return the data in Microsoft Office and choose the Pivot Table Report
option when asked.

Now you can play
with the Pivot Table functionality provided by Excel. To do so, you drag and
drop fields listed in the field list into the Filter, Row Labels, Column
Labels, and Values areas. The table below shows quantities obtained by pivoting
on Month and CompanyNumber.

Experiment with the
PivotTable to answer the following questions:
7. What product sold
the most items in Company 4?
8. What item brought
in the most money in Company 3?
9. Which was your
biggest seller (most money) in March overall?
Write all answers to yourlastname_Lab2.doc.
Take a screen shot of the Pivot Table you
used to answer Question 9 and add it to yourlastname_Lab2.doc
Write your Select
query for to yourlastname_Lab2.doc.
11 (Extra credit). In SQL Server, write the SQL SELECT query
to find the PName of the product that was the biggest seller in terms of money
in March (should obtain the same answer as for Question 9). Write
your Select query to yourlastname_Lab2.doc.
Turn in:
Electronic:
Hard-copies: