Hello Team,

I am working with a dataset that includes a date field (for example, Order_Date) and business metrics such as Sales.

Sample scenario:

• Order_Date: 2023-01, 2023-02, 2023-03, 2024-01

• Metric: Sales Amount

Use case:
I want to compare the current period’s value with a previous or next period, such as:

• Current month sales vs previous month sales

• Current month sales vs same month in the previous year

I understand that Lag and Lead (Leap) functions can be used for such period-based comparisons, but I would like clarity on how these functions should be correctly framed and applied in Lumenore, especially with respect to:

• Required date sorting or date hierarchy

• Appropriate use cases for Lag vs Lead (Leap)

• Whether these functions are best applied at the dataset level or dashboard level

Could you please share the recommended approach or best practices for using Lag and Lead (Leap) functions in this type of time-based analysis?

Hello Team,

I am working with a dataset that contains transactional data with a date column (for example, Order_Date) and business metrics such as Sales.

Sample scenario:

• Order_Date: 2023-01-15, 2023-02-10, 2024-01-20

• Metric: Sales Amount

Use case:
I want to analyze:

• Month-over-Month (MOM): Comparison of sales for Feb-2023 vs Jan-2023

• Year-over-Year (YOY): Comparison of sales for Jan-2024 vs Jan-2023

While the date field is already present in the dataset, I would like to understand how YOY and MOM requirements should be framed correctly in Lumenore, especially in terms of:

• Using date hierarchies (Year / Month)

• Choosing between dataset-level vs dashboard-level calculations

• Handling scenarios such as partial months or missing dates

Could you please share the recommended approach or best practice for defining YOY and MOM analysis in this context?

I have created multiple datasets in Lumenore but I want to create a join schema using tables of these dataset how can I do so