Modern Data Management & Business Intelligence

Assignment 2 for the Data Management and Business Intelligence Course of AUEB's MSc in Business Analytics.

Description

In this assignment, you will utilize SQL Server Database, SQL Server Analysis Services, and Power BI or Tableau to design and develop a data warehouse, build data cubes, develop OLAP reports, and visualize the results. The project presentation will be conducted in Teams with each group allocated 10-15 minutes. The presentation should be in the form of a business case and include:

• Business goals and description of the problem/domain
• Description of data sources and where the datasets were obtained
• Design of the data warehouse, cubes, etc.
• Import/cleaning/transformation challenges and solutions
• Examples of OLAP queries, reports, etc.
• Visualization examples

Try to narrate your presentation as a story, putting yourself in the shoes of the storyteller!

Steps:

1. Find a Dataset:

   • Explore datasets from various sources such as Kaggle, GitHub, KDnuggets, Data.gov, or through Google searches for datasets related to data warehousing, data mining, OLAP, etc.

2. Understand Facts and Dimensions:

   • Define a star/snowflake schema in your SQL Server database.
   • Populate the fact and dimension tables from the chosen dataset, possibly by using the import task in your database server. You may need to clean, transform, or manually define dimension tables.

3. SQL Server Analysis Services:

   • Utilize SQL Server Analysis Services to define a multi-dimensional model (a cube) over your schema.
   • Explore the reporting capabilities of your tool and showcase OLAP reports, including drill down/roll up, pivoting, ranking, etc.

4. Power BI Installation:

   • Install Power BI and utilize your database schema to demonstrate OLAP examples and visualize the data. Aim for creative and interactive visualizations to enhance your presentation.

Deliverables:

• A document (.doc or .pdf) detailing each step of the project:
  • Description of the targeted application, dataset used, sources, problems addressed, and analysis goals.
  • Description of the relational design of fact and dimension tables, import methods, cleaning/transformation procedures.
  • Details about the built cube, dimensions, measures, and any calculated measures in English.
  • Description and screenshots of OLAP reports, along with visualizations and explanations of their production.