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In the previous post, we explored how to calculate cumulative sales and ABC classification by brand using the simplest and most intuitive RUNNINGSUM function. However, in business practice, beyond simple end-to-end accumulation, various calculation requirements arise depending on the analytical objective. "What if you only want to calculate the total sales for the top 3 brands?" "What if you want to group and calculate only the previous step and the current step together?" Moments like these inevitably arrive when you need to freely control the calculation boundary (sliding window). The master key in Visual Calculations for these scenarios is the WINDOW function. In Part 2, based on the same brand sales data, we will examine the powerful control of the WINDOW function and how it carves out visual space to execute calculations. [Link] [Go to Power BI Visual Calculation Part 1: RUNNINGSUM] Basic Example Data 1. Understanding the St...

In this article, we will examine how to implement cumulative sales (Running Total) by brand utilizing the RUNNINGSUM function provided in Power BI Visual Calculations. In this example, we analyze the cumulative sales trend across brands based on consumer electronics sales data. 1. Example Data The brand names and sales data below are fictional data created solely for illustrative purposes and bear no relation to the actual sales performance of any company. Brand: Apple / Total Sales: $25,000 Brand: Samsung / Total Sales: $13,000 Brand: Sony / Total Sales: $5,000 Brand: Xiaomi / Total Sales: $3,500 Brand: LG / Total Sales: $1,500 Brand: Huawei / Total Sales: $1,200 Brand: Lenovo / Total Sales: $800 The purpose of this example is not simply to verify brand sales rankings. In practical business analytics, we must address the following strategic questions: "Do the top few brands account for the vast majority of overall r...

In our previous post, we explored how to calculate Year-over-Year (YoY) growth using the OFFSET function, and how to combine it with PARTITIONBY to prevent reference errors when monthly data is missing. This time, we will examine INDEX , another core function available within Visual Calculations. While OFFSET is a function that navigates to a relative row based on the current position, INDEX is a function that directly references a row at a specified sequence number. This is highly useful for analyses that require comparing against a fixed baseline data point or finding starting and ending points. In this article, we will unpack the operational mechanics of the INDEX function alongside a YoY calculation example, and summarize the critical production-grade limitations that you must understand in practice. Previous post Calculating Year-over-Year (YoY) Growth Using SUMX + FILTER in the New Power BI Visual Calculations Calculating Yea...

In our previous two posts, we explored how to calculate Year-over-Year (YoY) growth utilizing Power BI’s innovative new feature, Visual Calculations. • First Post: We examined how to deploy ROWS and SUMX to directly navigate and locate prior-year same-month data within the current visual. • Second Post: We implemented the identical analytical result by leveraging the WINDOW function to reference data exactly 12 rows prior relative to the current row. However, within Visual Calculations, there are other highly potent functions belonging to the Window Function family besides WINDOW. These are OFFSET and INDEX. In many practical scenarios, OFFSET is vastly more intuitive than WINDOW, and INDEX becomes far more useful when you need to pinpoint an absolute position. In this article, we will completely implement the identical Year-over-Year (YoY) growth metric...

In our previous discussion, we calculated Year-over-Year (YoY) growth by utilizing ROWS and SUMX to directly search for matching prior-year data within the current visual. However, the powerful capabilities of Visual Calculations do not end there. As Power BI has expanded this new feature set, we can now leverage Window Functions such as WINDOW, OFFSET, and INDEX. While the previous approach can be defined as "finding data via logic and conditions," utilizing a Window Function is "referencing data based on its relative position." Even though both methods produce identical results, the analytical lens and calculation mechanisms are fundamentally altered. To be frank, it is not strictly mandatory to deploy this method for your everyday YoY calculations. Nonetheless, the reason we must implement this function firsthand is clear: it broadens our data-mod...

When building production dashboards with Power BI, one of the most frequently implemented core metrics is Year-over-Year (YoY) growth. Traditionally, achieving this required combining complex DAX functions such as CALCULATE, SAMEPERIODLASTYEAR, and ALL. In particular, if the data model's relationships or Date Table configurations were not absolutely flawless, incorrect values would often surface—causing significant headaches for beginners and intermediate users alike. However, the introduction of the new 'Visual Calculation' feature in Power BI has completely changed the game. Instead of navigating through the entirety of a complex data model, users can now intuitively perform calculations by treating the visualization table (the visual) currently displayed on the screen as its own independent database. In this post, without relying on intricate time intelli...