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IMAT5167 Data Warehouse Design And OLAP

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  • Course Code: IMAT 5167
  • University: De Montfort University
  • Country: United Kingdom


Scenario: Midlands Theatre (MT) Company

Company Overview:

Midlands Theatre (MT) is a chain of small theatres that are found within the suburbs of several cities and towns within the Midlands, including Leicester and Birmingham. It specialises in high quality theatre productions that may be seen to be insufficiently “mainstream” for the general population. The company purchased its first theatre in January 1982, and since then has seen substantial increases in the number of clients that want to visit a local theatre to see a production that is more alternative to those typically found within the city centre theatres and/or large entertainment complexes. In response to the growing client base, MT sometimes offers a matinee (i.e., afternoon) performance of a popular production in addition to the traditional evening performance time.

Alongside the increase in number of theatre goers comes the issue of managing the additional bookings and ticketing requirements. The Managing Director of MT, Ms. Heritage, has decided that a computerised booking system for MT is needed. Although the ultimate aim is to enable the on-line booking of tickets for any MT productions at any MT theatres, Ms. Heritage would like a simple booking system to be created first. This first version booking system will automate the existing manual booking processes, which are detailed below.

Information regarding current booking processes at Midlands Theatre (MT):

Each of the theatres in MT’s portfolio has a schedule of productions for a given month in a particular calendar year. For instance, a schedule for a production entitled “Wind Blows”, which ran for one week at the Cropston Theatre during March 2018, is provided in Table 1.

Table 1.  Example of one week performance at the Cropston Theatre

Name of Production

Day and Date



“Wind Blows”

Scriptwriters: William

Director: Henry

Monday 7/3/2018

No performance



Tuesday 8/3/2018

No performance



Wednesday 9/3/2018




Thursday 10/3/2018

No performance



Friday 11/3/2018




Saturday 12/3/2018




Sunday 13/3/2018

2pm – note earlier start

6.45pm – note earlier start


Only one production is shown at a theatre at a time, and some of the more popular productions run both afternoon (matinee) and evening performances.

Productions could be at a theatre for several weeks, although the majority of productions run only for a few days over one week. The run of the next production cannot start until the previous production has ended (in other words there is no interleaving of the performance runs of different productions).  It is common for the same production to have runs in all of MT’s theatres - one theatre after another - so that the widest number of potential clients for a production is reached.

When a potential theatre goer wants to purchase a ticket for a particular performance of a production at a MT theatre in advance, s/he contacts the central booking service via the website, telephone or an App. Whenever a ticket is purchased, a unique purchase number is allocated, the performance to be attended, the theatre, the client details (such as name, postcode and house number, and telephone), the total amount paid and the method of payment (cash, Paypal, debit card or credit card) and the method of ticket delivery (either by mail/email or by client pick up from the local theatre box office) are recorded. If several tickets are bought at the same time by the same person, each ticket is recorded as if it were bought separately.  

Table 2. Further Information about each Entity (Type) on the EER Diagram

Entity Type

Entity Instance


A particular MT theatre e.g., Cropston


A particular production e.g., How the Wind Blows


A particular performance of a production run, e.g., a performance of Wind Blows at Cropston Theatre on Monday 7/3/18 at 7.30pm


A particular client of a theatre e.g., Mr Eric Charles


A particular ticket bought for a particular performance e.g., Ticket Purchase No. 29, which is for Cropston Theatre for the 9/3/18 performance  at 7.30pm of  Wind Blows and is bought by Ms Helen w2544.

Any remaining tickets for a performance are available to buy on the day from the local theatre box office. The same details are recorded, although clearly in this case the ticket will always be collected from the local theatre box office!

A relational database has been created according to the ERD.  The tables

are as follows:

  • Theatre(Theatre#, Name, Address, MainTel);
  • Production(P#, Title, ProductionDirector, PlayAuthor);
  • Performance(Per#, P#, Theatre#, pDate, pHour, pMinute, Comments);
  • Client(Client#, title, name, address, telNo, e-mail);
  • TicketPurchase(Purchase#, Client#, Per#, PaymentMethod, DeliveryMethod, TotalAmount).

Having established the online transaction processing database, Ms. Heritage wants more intelligence information from the available data and she is looking for a potential data warehouse for MT.  As the first step in this process, she expects to setup a data mart for ticket sales as the first step.  The data mart should satisfy the following analysis requirements:

  • Yearly total sale for each theatre.
  • All clients who visited MT theatres in at least 4 different months in a year.
  • List the titles, production directors and play authors of all products with the highest total sale.

Here, by ticket sale value, we refer to the value of money rather than number of tickets.  For this data mart, only the data involved in ticket sales are stored, and any data not involved in at least one ticket sale should not be included.

You can access the OLTP database in my database schema: ops$yyang00.  For example, you can access the data for Theatres using the following SQL statement:

select * from ops$;

Your Tasks

You are to develop a prototype of ORACLE data mart for ticket sales as a part of a potential data warehouse for MT.  For this assignment you are required to work individually.

You have been given the MT company scenario, together with an Extended Entity Relationship (EER) Diagram and corresponding tables for the existing relational database. 

Task 1: Analyse the given database design and the requirement for data mart, identify the dimensions and fact for your data mart  

Task 2: Design the star schema for the data mart and identify the corresponding PKs and FKs  

Task 3: According to given data and requirements, determine the relevant attributes and suitable granularity in your data mart  

Task 4: Map your star schema to logical relations  

Task 5: Create the corresponding tables in Oracle using SQL

Task 6: Identify your source data from the OLTP database and design your data extraction rules.  You need to give a detailed mapping and transformation list from the source to the destination.

Task 7: Implement your data extraction, transformation and loading through Oracle SQL.  The number of rows extracted into each dimension or fact table in your data mart should be printed from Oracle query.

Task 8: Comment on how your data mart satisfies the requirements of MT.  Implement the required data analysis requirements for both data mart and the original OLTP database.  Compare your queries and comments on the advantages of data mart in analysis operations. Test results from Oracle query should be included.

Evidence of the successful execution of your queries is required.  For large outputs, you need to provide only the last page of outputs with the number of rows in the end.

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