Data Warehouse Project Assignment

Assignment Task

Project

1. Data Warehouse Design

Project Contributes to the total assessments of this unit as an individual effort. The deadlines are recorded on submission.

The overall objectives of this project are to build a data warehouse from real-world datasets and to carry out a basic data mining activity, in this case, association rule mining.

Datasets and Problem Domain

Prescribed datasets: the source data to design and populate the data warehouse in this project is based on the Olympic Dataset.

The Olympic Games represent the sole global, multi-disciplinary sports event, celebrated worldwide. Featuring participation from over 200 nations in more than 400 events spanning both the Summer and Winter Games, the Olympics serve as a platform for global competition, inspiration, and unity.

Data Warehousing Design and Implementation

Following the four steps below of dimensional modelling (i.e. Kimball's four steps), design a data warehouse for the dataset(s).

1. Identify the process being modelled.

2. Determine the grain at which facts can be stored.

3. Choose the dimensions

4. Identify the numeric measures for the facts.

To realize the four steps, we can start by drawing and refining a StarNet with the above four questions in mind.

1. Think about a few business questions that your data warehouse could help answer.

2. Draw a StarNet to identify the dimensions and concept hierarchies for each dimension. This should be based on the lowest level of information you have access to.

3. Use the StarNet footprints to illustrate how the business queries can be answered with your design. Refine the StarNet if the desired queries cannot be answered, for example, by adding more dimensions or concept hierarchies.

4. Once the StarNet diagram is completed, draw it using software such as Microsoft Visio (free to download under Azure Education) or a drawing program/website of your own choice. A Hand-printed StarNet diagram is also welcome! Paste it onto an Atoti/Power BI Dashboard.

5. Implement a star or snowflake schema using SQL Server Management Studio (SSMS), or PostgreSQL, or other software. For the fact table and dimension tables, clearly state which ones are measures and dimensions, and indicate the dimension references.

6. Use Atoti to build a multi-dimensional analysis service solution, with a cube designed to answer your business queries. Make sure the concept hierarchies match your StarNet design.

7. Use Power BI/Atoti to visualise the data returned from your business queries.

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