When designing a data warehouse or a dimensional model, it’s common to encounter situations where a dimension can have multiple hierarchies. These alternate hierarchies represent different ways of organizing and analyzing the data within the dimension.

Handling alternate hierarchies correctly is crucial for providing users with flexible and meaningful ways to slice and dice the data. In this blog post, we will discuss some techniques for effectively managing alternate hierarchies in dimension tables.

1. Separate Table Approach

One approach to handling alternate hierarchies is to create separate dimension tables for each hierarchy. Each table would contain the necessary attributes and relationships specific to that hierarchy. This technique allows for easy navigation and querying of each hierarchy independently.

By separating hierarchies into distinct tables, it becomes easier to manage and understand the relationships between attributes within each hierarchy. Additionally, this approach provides the flexibility to add or remove hierarchies without disrupting the existing data model.

Example code:
CREATE TABLE dim_product (
  product_id INT,
  product_name VARCHAR(100),
  product_category_id INT,
  product_subcategory_id INT,
  ...
);

CREATE TABLE alt_hierarchy_1 (
  product_id INT,
  hierarchy_1_attr_1 VARCHAR(100),
  hierarchy_1_attr_2 VARCHAR(100),
  ...
);

CREATE TABLE alt_hierarchy_2 (
  product_id INT,
  hierarchy_2_attr_1 VARCHAR(100),
  hierarchy_2_attr_2 VARCHAR(100),
  ...
);

#datawarehousing #dimensionmodelling

2. Attribute-Based Approach

Another technique for handling alternate hierarchies is through an attribute-based approach. Instead of creating separate tables, this approach involves adding additional attributes to the existing dimension table to support different hierarchies.

The additional attributes would capture the relationships and hierarchies specific to each alternate hierarchy. By utilizing logical relationships through attributes, different hierarchies can be represented within a single table.

Example code:
CREATE TABLE dim_product (
  product_id INT,
  product_name VARCHAR(100),
  product_category_id INT,
  product_subcategory_id INT,
  hierarchy_1_attr_1 VARCHAR(100),
  hierarchy_1_attr_2 VARCHAR(100),
  hierarchy_2_attr_1 VARCHAR(100),
  hierarchy_2_attr_2 VARCHAR(100),
  ...
);

The attribute-based approach simplifies the data model by keeping all hierarchies within one table. It allows for more efficient storage and retrieval of data and reduces the complexity of managing multiple tables.

Both the separate table approach and attribute-based approach have their advantages and considerations. The choice depends on factors such as the complexity of hierarchies, data volume, query performance, and flexibility requirements.

In conclusion, handling alternate hierarchies in dimension tables requires careful consideration and selection of appropriate techniques. By implementing the right approach, data warehouse designers can create flexible and user-friendly models that effectively support the analysis and reporting needs of the organization.

#datawarehousing #dimensionmodeling