Author Archives: alapitsk

First Month Gifts Using Generate Function

Posted on December 28, 2021 by alapitsk

Often we need to derive first-month sales/donations. In the sample dashboard that I built using public FEC data, there are donors with multiple donations. The formula below allows determining donations in the first month since the first donation in a … Continue reading →

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Donors With Multiple Gifts

Posted on December 20, 2021 by alapitsk

Often we need to derive donor with multiple gifts grouped by other dimensions. In the example below, I am adding a count of donors in a specified range from a zip code who made multiple donations. The dashboard example is … Continue reading →

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Adding Contribution Range Visual

Posted on November 27, 2021 by alapitsk

It is often useful too add a gift bracket and then pivot and visualize those ranges. In the example below, I am adding a gift range and then visualizing what kind of gifts (small – large) generated most of the … Continue reading →

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Using CrossFilter To Alter Relationship

Posted on November 14, 2021 by alapitsk

I recently came over an example of CROSSFILTER function in DAX. While not very common I can see a lot of potential in certain circumstances. Essentially, in a measure, it temporarily alters relationships. In most cases, there is a fact … Continue reading →

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DAX Retention Year Over Year Pattern

Posted on November 10, 2021 by alapitsk

Often we need to write many lines of code in SQL to derive retention year over year. Generally, we join the main fact table to itself and then add a condition that a donor this year has to also be … Continue reading →

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Dynamic Donor Location Based On The Miles of Zip Code

Posted on October 4, 2021 by alapitsk

Here is an example of a dashboard that I created using public FEC data. The data is similar to many donor and sales files. The dashboard will allow you to pick donors based on proximity to a selected zip code. … Continue reading →

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Cleaning Up Tabular Models

Posted on September 26, 2021 by alapitsk

When I started at my current job, much of the new Power BI development occurred in one giant tabular model. At some point, the model had almost 1200 measures. Having so many measures in the model made it hard to … Continue reading →

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