2023 The second assignment focuses on the agility of data warehouse developments redesigning an existing dimensional model and the | Assignment Collections

Computer Science 2023 BUS5WB – Data Warehousing And Big Data Assignment 02: OLAP, Cubes, And Insights

2023 The second assignment focuses on the agility of data warehouse developments redesigning an existing dimensional model and the | Assignment Collections

The second assignment focuses on the agility of data warehouse developments, redesigning an existing dimensional model, and the use SSDT tools and techniques to generate business insights. Your ability to correctly apply these tools to a business use case will be assessed.

Task 1: Agile data warehouse development approach

Conduct a critical evaluation of the dimensional models that you designed in assignment 01 to formulate an agile development approach for the corresponding data warehouses. The lecture on data warehouse lifecycle provides a basis for this formulation but you are required to reference external reading on agile and cloud data warehouse solutions (preferably Azure) to determine the critical components that will address the business needs with agile delivery.

The following business case applies to Tasks 2 and 3: 

The CIO of Valeur, a large national supermarket/retail store chain has recently introduced a loyalty card program and keen to gain a more comprehensive understanding of the organisation’s customer base through traditional transactional data as well as the newer and effective demographic analysis techniques. The customer relationship management (CRM) team working under her supervision have already put together a summarised data warehouse containing some transaction data and customer demographics. Although the data is accurate and complete, the CIO believes the structure is not. She feels there’s more information that can be captured by the warehouse. She has two main business problems in mind. Firstly, improving the current dimensional model/ warehouse to capture all relevant information that applies to customers, such as demographics. Secondly, using current data in the warehouse to better understand the customer base by identifying customer behaviours and thereby potential sales and marketing opportunities.

Task 2: Dimensional model redesign

Study the given dimensional model to determine what is lacking in response to the business need. Identify potential improvements to the dimensional model. This can be in the form of new attributes, new dimensions, new measures or the use of dimension design techniques. Present your recommendations with supporting evidence and the new dimensional model.

Task 3: Demonstration of Analysis Tools

The data warehouse (ValeurDW) is accessible from the WB server.

Use the knowledge and experience gained from tutorials 7-10, to demonstrate each of the seven analysis

technique/tool – 1) SSAS, 2) Cube Features, 3) SSRS, 4) MDX, 5) SSDT Data mining, 6) Excel Power Pivot, and 7) PowerBI, by conducting a comprehensive analysis of customer behaviours and thereby potential sales and marketing opportunities.

It is anticipated that you will demonstrate your proficiency with advanced analysis approaches rather than simple and straightforward querying. Each demonstration should lead towards an insight/recommendation of business value. A minimum of seven demonstrations is expected, preferably in increasing complexity and increasing decision value.

 

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