7/4/2023 0 Comments Anomaly youtubeFor example, it's the ratio of actual minus expected value, between the component time series Fabrikam and the aggregate time series overall Revenue for the anomaly point. Power BI calculates strength as the ratio of the deviation from expected value, when filtered by the dimension to the deviation in total value. Here, seller "Fabrikam" has a strength of 99%. In this case, the anomaly on August 31 seems to be associated with a particular seller and particular cities. For example, by dragging Seller and City into the Explain by field well, Power BI restricts the analysis to just those fields. You can also control the fields that are used for analysis. I can open the cards in this pane to see more details of the explanation. Here I see that on August 30, Revenue was $5187, which is above the expected range of $2447 to $3423. It gives you a natural language explanation of the anomaly, and factors associated with that anomaly, sorted by its explanatory strength. When you select the anomaly, Power BI runs an analysis across fields in your data model to figure out possible explanations. If you decrease the sensitivity, the algorithm is more selective on what it considers an anomaly.īesides detecting anomalies, you can also automatically explain the anomalies in the data. In that case, even a slight deviation is marked as an anomaly. If you increase the sensitivity, the algorithm is more sensitive to changes in your data. You can also configure the parameter of the algorithm. You can format the anomaly's shape, size, and color, and also the color, style, and transparency of expected range. Check out this technical blog for more details about the Anomaly Detector algorithm. When a value goes outside this expected boundary, it's marked as an anomaly. Adding anomaly detection automatically enriches the chart with anomalies, and the expected range of values. You can enable Anomaly detection by selecting the chart and selecting Find anomalies in the analytics pane.įor example, this chart shows Revenue over time. To follow along with this tutorial, download the sample file of an online-sales scenario. This tutorial uses online sales data for various products.
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