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Doing Time Intelligence in Power BI - A Review Case

This article is a brief review about how to develop Time Intelligence models in Power BI.  That said, this post is written for the reader who is new to the concept. Time intelligence is computing the standard used in calculations over periods of Time or Dates. Typical examples of Time Intelligence: Aging Aging is to break down calculations over periods of time.  A noteworthy example is the Aged order backlog that renders 'open customer orders' by shipping date or an original acknowledge the date. Period to Date Period to date is the sum total of a metric during a period.   *         Revenue Quarter to date *         Inventory Receipts month to date *         Quarter to date Mobile phone costs Comparisons Comparisons juxtapose two similar periods of time for a given metric. Almost always these comparisons are outlined as a percentage. *         Year over Year Sales *         On-time performance vs. the previous month *         Standard hours earned
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What is quick Measure?

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A Quick measure could be a fast way to produce a DAX measure! That’s why it's known as so! This is often seen as one in all of the simplest scenarios of naming a feature, it's obvious. Ought you to have a special setup to use quick measures? Let’s see how it works. Reminder concerning quick Measures in Power Bi Before we tend to dive into some examples, let us simply offer you a friendly reminder that whereas it's terribly simple to use, quick measures isn’t perfect. However the great news is that it’s being updated all the time. The Power Bi team have created a superb call of desirous to automatize the maximum amount of the event around Power Bi models as potential that is nice. Misconceptions Quick Measures work with Default or Custom Date Dimension There is a typical idea that says fast measures solely work with the custom date dimension, not with the default one. This is often not true. As you see in higher than it works absolutely with the default Date dimension, and
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