Unleashing the Power of SSAS Cubes: Creating a Derived Column from 2 Dimensions

Are you tired of dealing with cumbersome data models and complex calculations in your SSAS cubes? Do you wish there was a way to simplify your analysis and gain deeper insights into your data? Look no further! In this article, we’ll show you how to create a derived column from 2 dimensions in SSAS cubes, unlocking a world of possibilities for your business intelligence endeavors.

What is a Derived Column in SSAS Cubes?

A derived column is a calculated column that combines data from one or more tables or dimensions in your SSAS cube. It allows you to create new columns that don’t exist in your original data source, enabling you to perform advanced calculations, concatenations, and aggregations. In essence, derived columns empower you to transform your data into meaningful insights, making it easier to analyze and make informed decisions.

Why Create a Derived Column from 2 Dimensions?

Creating a derived column from 2 dimensions offers numerous benefits, including:

• Simplified Data Modeling: By combining data from multiple dimensions, you can reduce the complexity of your data model, making it easier to manage and maintain.
• Enhanced Analysis: Derived columns enable you to perform advanced calculations and aggregations, revealing hidden patterns and relationships in your data.
• Improved Data Quality: By creating derived columns, you can ensure data consistency and accuracy, eliminating errors and inconsistencies in your analysis.

Step-by-Step Guide to Creating a Derived Column from 2 Dimensions in SSAS Cubes

Now that we’ve covered the basics, let’s dive into the nitty-gritty of creating a derived column from 2 dimensions in SSAS cubes. Follow these steps to get started:

Step 1: Create a New Calculated Column

In your SSAS cube, navigate to the Calculations tab and click New Calculated Column. This will open the Calculated Column editor.

  
    // Create a new calculated column
    CREATE COLUMN [Derived Column] AS 
    (
      // Your calculation goes here
    )
  

Step 2: Define the Calculation

In the Calculated Column editor, define the calculation that will combine data from the two dimensions. For example, let’s say you want to create a derived column that concatenates the Product Category and Product Subcategory dimensions:

  
    // Concatenate Product Category and Product Subcategory
    CREATE COLUMN [Derived Column] AS 
    (
      [Product].[Product Category] + ' - ' + [Product].[Product Subcategory]
    )
  

Step 3: Specify the Data Type

In the Calculated Column editor, specify the data type for the derived column. In this example, we’ll use the String data type:

  
    // Specify the data type
    CREATE COLUMN [Derived Column] AS 
    (
      [Product].[Product Category] + ' - ' + [Product].[Product Subcategory],
      DataType = 'String'
    )
  

Step 4: Deploy and Process the Cube

Once you’ve defined the calculation and specified the data type, deploy and process the cube to make the derived column available for analysis.

Common Scenarios for Derived Columns from 2 Dimensions

Derived columns from 2 dimensions can be used in a variety of scenarios, including:

• Geographic Analysis: Create a derived column that combines country and region dimensions to perform geographic analysis.
• Product Hierarchy: Concatenate product category and product subcategory dimensions to create a product hierarchy.
• Date Calculations: Create a derived column that combines date and time dimensions to perform advanced date calculations.

Tips and Tricks for Working with Derived Columns

When working with derived columns, keep the following tips and tricks in mind:

1. Use meaningful names: Choose names that clearly indicate the purpose of the derived column.
2. Keep it simple: Avoid complex calculations that may impact performance or make the derived column difficult to maintain.
3. Test and validate: Verify that the derived column is working as expected by testing it with sample data.
4. Document your calculations: Keep track of your calculations and assumptions to ensure transparency and maintainability.

Conclusion

Creating a derived column from 2 dimensions in SSAS cubes is a powerful way to unlock new insights and simplify your data model. By following the steps outlined in this article, you can create derived columns that transform your data into meaningful information. Remember to keep your calculations simple, test and validate your results, and document your assumptions to ensure transparency and maintainability. With derived columns, the possibilities for business intelligence are endless!

Dimension 1	Dimension 2	Derived Column
Product Category	Product Subcategory	Product Category – Product Subcategory
Country	Region	Country – Region
Date	Time	Date – Time

Now, go ahead and unleash the power of derived columns in your SSAS cubes!

Frequently Asked Questions

Curious about derived columns from 2 dimensions in SSAS Cube? Get the answers to your burning questions here!