Register now to learn Fabric in free live sessions led by the best Microsoft experts. From Apr 16 to May 9, in English and Spanish.
Hi All,
Looking for an idea to understand how we can analyze in a large number of data to find Deviation Detection(
Analysis and detection of unusual data patterns that require further investigation)
I have 40000 records per day and the table contains 30 days of data, I want to identify the record which it deviated from its trend ( There is no defined threshold for this).
Any idea to implement in Power BI?
Solved! Go to Solution.
Hi nagoor,
You can create a scatter chart and click analysis panel-> add trend line to obverse the trend
After that, you can also right click on the table and add a quick measure(correlation variable) to measure the relation between the axis value you have plot on the scatter chart.
Reference: https://www.blue-granite.com/blog/simple-linear-regression-in-power-bi, http://powerbipro.com/regression-in-power-bi/
For more complex solution, you can also use Python visual or R visual in power bi to achieve your requirement, refer to this documentation about how to use python in power bi.
Regards,
Jimmy Tao
Hi nagoor,
You can create a scatter chart and click analysis panel-> add trend line to obverse the trend
After that, you can also right click on the table and add a quick measure(correlation variable) to measure the relation between the axis value you have plot on the scatter chart.
Reference: https://www.blue-granite.com/blog/simple-linear-regression-in-power-bi, http://powerbipro.com/regression-in-power-bi/
For more complex solution, you can also use Python visual or R visual in power bi to achieve your requirement, refer to this documentation about how to use python in power bi.
Regards,
Jimmy Tao
Covering the world! 9:00-10:30 AM Sydney, 4:00-5:30 PM CET (Paris/Berlin), 7:00-8:30 PM Mexico City
Check out the April 2024 Power BI update to learn about new features.
User | Count |
---|---|
109 | |
98 | |
77 | |
66 | |
54 |
User | Count |
---|---|
144 | |
104 | |
101 | |
86 | |
64 |