Requirement Gathering qsns

1. What exactly is the business need for the feature?
2. Why is this feature needed?
3. What is the desired outcome?
4. How often will this feature be used?
5. What is the business value of this feature?
6. What is the expected end result?
7. What will classify that the requirement has been met?
8. What workarounds are available?
9. Will it be possible to do without certain features?

 

3. How will you use the system? 

1. What triggers the start of your interaction with the system/feature? 
2. What are the handoffs? 
3. What are the business rules? 
4. What is your happy path? 
5. What is your alternate path

 

Why do BAs need to gather/elicit requirements?

          Investigation of general concern 

Diagnose weaknesses in a business process 

Investigate & compile requirements for the system 

Stakeholders are unaware of existing alternatives 

Stakeholders are resistant to change 

Different Stakeholder perspectives 

Techniques available depend on project size, location, 

Investigate & compile requirements 

 

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Requirements gathering  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!

 

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 food delivery dimensional data model

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When gathering requirements for a food delivery dimensional data model, the focus should be on business needs, data sources, and operational insights specific to the industry. Here's a guide to help you:

Business Requirements

• What are the main business objectives for this model (e.g., optimizing delivery times, analyzing customer trends)?
• What types of reports or dashboards are needed (e.g., delivery performance, order frequency)?
• Who are the primary users of the model (e.g., operations teams, marketing teams)?
• What key metrics should be tracked (e.g., average delivery time, order value, customer ratings)?

Data Sources

• What are the primary data sources (e.g., customer database, order management system, delivery tracking system)?
• Are there external data sources, such as traffic or weather data?
• How often is data updated, and is real-time processing required?
• Is historical data important for trend analysis? If so, how much history is needed?

Technical Considerations

• What is the existing infrastructure for data processing and storage?
• Are there any technical constraints or integration challenges with source systems?
• What security measures are required to protect sensitive data (e.g., customer addresses, payment details)?
• What is the expected volume of data, and how should it scale?

Dimensional Modeling Specifics

• What are the key dimensions (e.g., customer, time, delivery partner, restaurant)?
• What measures should be included (e.g., delivery distance, order total, delivery time)?
• Are there hierarchies within dimensions (e.g., geographic regions, meal categories)?
• How will the model handle changes over time (e.g., updated customer preferences)?

Validation and Maintenance

• How will the model be tested for accuracy and reliability?
• Who will oversee updates and maintenance of the model?
• Are there anticipated future expansions or new features (e.g., predictive analytics)?

These questions ensure your data model supports operational efficiency and business insights. Let me know if you'd like to dive deeper into any aspect!

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