IGLOO BI

Analyzing Growth Gaps with Cumulative YoY (Periodic Comparison) The most frequent question that pops up in business reporting is this: "Our cumulative sales through November hit $500k... but are we actually doing better than last year?" Simple month-over-month YoY comparisons are heavily influenced by seasonality and promotion timing. However, Cumulative YoY compares the actual growth velocity, showing the true trajectory of your business much more accurately. In this tutorial, you will learn how to create a Cumulative YoY (Year-over-Year) growth analysis in Power BI using the DAX ALL function and week-based filtering.   1. Practical Example Data Structure We will use the same example from Part 2: Selective Accumulation. The accumulation baseline is set to Week 27 (W27), which marks the start of the second half of the year, rather than a specific calendar date. For a detailed look at the data structure, please refer to [Link - Part 2 Selective Accumulation]. ① 2023 Sales Dat...

In our previous post, we explored the structure of a standard Running Total that accumulates from the beginning of the year. While standard Power BI functions like TOTALYTD are convenient, they have limitations when an analyst needs to start accumulation from an "arbitrary point in time." In this guide, we will explore how to create selective accumulation in Power BI using the DAX ALL function. In practice, there are many more occasions where you need to track performance starting from the day a specific campaign or event began, such as: "What was the initial performance since the new product launch?" "How much revenue was accumulated specifically during the Black Friday campaign period?" The core of this part is understanding the calculation logic that breaks the existing flow of time and rebuilds energy from a designated Baseline by utilizing the "Table Provider" role of the ALL function.   1. Practical Example: Capturing 'Cumulative Imp...

In our last post, we theoretically explored how the ALL function releases time filters to set the stage for accumulation analysis. Today, we move into the practical application: implementing a Running Total using real-world IT device sales data and interpreting it through the lens of business strategy. If your professional dashboard only shows monthly sales charts, it’s like checking only the "instantaneous speed" of a car. A Running Total, however, is the "odometer" that shows how far you have traveled toward your destination. Especially in organizations with annual quotas, accumulation data is more than just a performance report—it is the most powerful basis for deciding whether to commit additional resources in the second half of the year.   1. Practical Example Data Structure We will design basic measures based on the provided July to December data. Base Measure: Total Sales = SUM(Sales[Sales]) Total Volume: $3,259,000 (Total for the second half)   2. Why ...