gathering requirements for a banking dimensional data model

 

When gathering requirements for a banking dimensional data model, it's essential to ask questions that cover business needs, data sources, and technical aspects. Here are some key areas to focus on:

Business Requirements

• What are the primary business objectives for this data model?
• What types of reports or analyses will this model support (e.g., customer segmentation, transaction trends)?
• Who are the end-users of this data model (e.g., analysts, managers)?
• What key performance indicators (KPIs) should the model track?

Data Sources

• What are the main data sources (e.g., transaction systems, customer databases)?
• Are there any external data sources (e.g., market data, regulatory data)?
• What is the frequency of data updates (real-time, daily, weekly)?
• Is historical data required? If so, how far back should it go?

Technical Considerations

• What is the existing technical architecture? Are there any constraints?
• What data formats and structures are used in the source systems?
• Are there specific security or compliance requirements for the data?
• What is the expected volume of data, and how should it be handled?

Dimensional Modeling Specifics

• What are the key dimensions (e.g., customer, product, time)?
• What measures or metrics should be included (e.g., transaction amounts, account balances)?
• Are there any hierarchies within dimensions (e.g., geographic regions, product categories)?
• How should the model handle changes over time (e.g., slowly changing dimensions)?

Validation and Maintenance

• How will the model be validated to ensure accuracy?
• Who will be responsible for maintaining the model after implementation?
• Are there any anticipated changes or expansions to the model in the future?

These questions can help ensure that the dimensional data model aligns with business goals and technical requirements. If you'd like, I can dive deeper into any specific area!