How can you design effective hierarchies in dimensional modeling?

1 Define clear and consistent hierarchies

The first step to design effective hierarchies is to define them clearly and consistently. You should identify the most relevant and meaningful dimensions and levels for your business domain and use descriptive names for them. For example, if you have a product dimension, you might have levels such as product line, product category, product subcategory, and product name. You should also ensure that each level is unique and mutually exclusive, meaning that each member of a level belongs to only one parent in the higher level. For example, if you have a geography dimension, you should not mix countries and regions in the same level.

2 Balance the depth and breadth of hierarchies

The second step to design effective hierarchies is to balance the depth and breadth of them. The depth of a hierarchy is the number of levels it has, and the breadth is the number of members in each level. You should avoid creating hierarchies that are too deep or too broad, as they can affect the performance and usability of your data warehouse. Too deep hierarchies can result in long drill-down paths and complex queries, while too broad hierarchies can result in large dimension tables and sparse fact tables. A good rule of thumb is to limit the depth of your hierarchies to four or five levels, and the breadth to less than 100 members per level.

3 Use conformed and role-playing dimensions

The third step to design effective hierarchies is to use conformed and role-playing dimensions. Conformed dimensions are dimensions that are shared and consistent across multiple fact tables, such as date, customer, or product. Conformed dimensions can help you integrate data from different sources and enable cross-fact analysis. Role-playing dimensions are dimensions that have multiple roles or meanings depending on the context, such as date, which can be order date, ship date, or delivery date. Role-playing dimensions can help you capture different perspectives and scenarios of your business processes. To implement role-playing dimensions, you can either create separate dimension tables for each role, or use a single dimension table with a role identifier in the fact table.

4 Consider alternative hierarchies and attributes

The fourth step to design effective hierarchies is to consider alternative hierarchies and attributes. Alternative hierarchies are hierarchies that have different structures or levels than the primary hierarchy, such as fiscal year versus calendar year for a date dimension, or geographic area versus sales territory for a geography dimension. Alternative hierarchies can help you accommodate different business requirements and analysis needs. Attributes are additional descriptive fields that are not part of the hierarchy, such as color, size, or price for a product dimension, or gender, age, or income for a customer dimension. Attributes can help you enrich your dimensions and provide more flexibility and detail for your analysis.

5 Validate and test your hierarchies

The final step to design effective hierarchies is to validate and test them. You should verify that your hierarchies are accurate, complete, and up-to-date, and that they conform to the business rules and logic. You should also test your hierarchies with sample data and queries, and check that they produce the expected results and performance. You should also solicit feedback from your end users and stakeholders, and make sure that your hierarchies are easy to understand and use. You should also be prepared to revise and refine your hierarchies as your business needs and data sources evolve.

6 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?