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PowerBI Attrition Dashboard for Monthly and yearly
Hi All,
I am trying to create monthly/Yearly PowerBI attrition. Following is data.
Attrition = (Total No of employee left for month/No of average employee for month)*100
Number of average employee = (no of employee at the start of the month + no of employee at the end of the month)/2
I want the output in the desired format
I saw three date columns in the data set: start date, end date, and date. Can you explain why the date column was used and where was the date column derived from?
Ashish_Mathur
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Hi,
Step into the Query Editor to see the transformation steps which i ran on the dataset.
Regards,
Ashish Mathur
http://www.ashishmathur.com
https://www.linkedin.com/in/excelenthusiasts/
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Hi,
When I put the month-end employees query, it is calculating I one extra employee under each country, not sure why.
Month end employees = CALCULATE([Employee count],DATESBETWEEN('Calendar'[Date],[Date since when data is available],[Date since when data is available]),USERELATIONSHIP('Employee Records'[Hire Date],'Calendar'[Date]))+[Hired till date]-[Left till date]
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Hi,
Study my previous file carefully. If the answers on that file are correct, then the answers on your live file should also be so. I d not know how else to help you.
Regards,
Ashish Mathur
http://www.ashishmathur.com
https://www.linkedin.com/in/excelenthusiasts/
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I did, I have put the calculations same as yours. In the month-end employees, it is giving me one extra count. I'm sure in some way you can help me, if you would like to 🙂
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Associate ID | Full Name | Hire Date/Rehire Date | Termination Date |
1 | Sample, 1 | 07/18/2011 | 02/01/2022 |
2 | Sample, 2 | 09/15/2011 | |
3 | Sample, 3 | 01/01/2008 | |
4 | Sample, 4 | 01/07/2008 | |
5 | Sample, 5 | 01/21/2008 | |
6 | Sample, 6 | 02/20/2008 | |
7 | Sample, 7 | 03/24/2008 | |
8 | Sample, 8 | 03/17/2008 | |
9 | Sample, 9 | 04/09/2008 | |
10 | Sample, 10 | 08/25/2008 | |
11 | Sample, 11 | 04/03/2009 | |
12 | Sample, 12 | 04/20/2009 | 03/04/2022 |
13 | Sample, 13 | 04/20/2009 | |
14 | Sample, 14 | 05/11/2009 | |
15 | Sample, 15 | 05/11/2009 | |
16 | Sample, 16 | 08/17/2009 | |
17 | Sample, 17 | 11/09/2009 | |
18 | Sample, 18 | 11/02/2009 | |
19 | Sample, 19 | 01/04/2010 | |
20 | Sample, 20 | 01/04/2010 | |
21 | Sample, 21 | 02/01/2010 | |
22 | Sample, 22 | 05/26/2010 | |
23 | Sample, 23 | 07/06/2010 | |
24 | Sample, 24 | 08/23/2010 | |
25 | Sample, 25 | 10/11/2010 | |
26 | Sample, 26 | 02/21/2011 | 02/01/2022 |
27 | Sample, 27 | 03/07/2011 | |
28 | Sample, 28 | 08/29/2011 | |
29 | Sample, 29 | 08/29/2011 | |
30 | Sample, 30 | 09/15/2011 | |
31 | Sample, 31 | 09/15/2011 | |
32 | Sample, 32 | 10/10/2011 | |
33 | Sample, 33 | 11/14/2011 | 05/13/2022 |
34 | Sample, 34 | 11/07/2011 | |
35 | Sample, 35 | 06/01/2014 | |
36 | Sample, 36 | 06/01/2014 | |
37 | Sample, 37 | 06/15/2009 | |
38 | Sample, 38 | 10/14/2013 | |
39 | Sample, 39 | 02/09/2009 | |
40 | Sample, 40 | 11/16/2009 | |
41 | Sample, 41 | 10/17/2008 | |
42 | Sample, 42 | 04/12/2010 | |
43 | Sample, 43 | 06/01/2010 | |
44 | Sample, 44 | 07/17/2006 | |
45 | Sample, 45 | 02/21/2011 | |
46 | Sample, 46 | 03/07/2011 | |
47 | Sample, 47 | 04/11/2011 | |
48 | Sample, 48 | 02/14/2007 | |
49 | Sample, 49 | 02/09/2007 | |
50 | Sample, 50 | 11/19/2016 | |
51 | Sample, 51 | 07/11/2022 | |
52 | Sample, 52 | 07/05/2011 | |
53 | Sample, 53 | 01/16/2014 | |
54 | Sample, 54 | 04/26/2019 | 04/25/2022 |
55 | Sample, 55 | 03/04/2019 | |
56 | Sample, 56 | 12/15/2016 | |
57 | Sample, 57 | 10/16/2006 | |
58 | Sample, 58 | 04/16/2018 | |
59 | Sample, 59 | 08/11/2022 | 03/08/2023 |
60 | Sample, 60 | 02/24/2017 | |
61 | Sample, 61 | 05/26/2015 | |
62 | Sample, 62 | 03/09/2016 | |
63 | Sample, 63 | 07/11/2022 | |
64 | Sample, 64 | 04/13/2016 | |
65 | Sample, 65 | 03/04/2022 | |
66 | Sample, 66 | 11/14/2016 | |
67 | Sample, 67 | 11/14/2018 | |
68 | Sample, 68 | 04/05/2022 | |
69 | Sample, 69 | 08/01/2014 | 06/01/2022 |
70 | Sample, 70 | 01/03/2017 | |
71 | Sample, 71 | 09/15/2008 | |
72 | Sample, 72 | 09/21/2016 | |
73 | Sample, 73 | 07/09/2012 | |
74 | Sample, 74 | 04/02/2012 | |
75 | Sample, 75 | 11/30/2022 | |
76 | Sample, 76 | 11/30/2004 | 11/01/2022 |
77 | Sample, 77 | 05/01/2020 | |
78 | Sample, 78 | 05/15/2017 | |
79 | Sample, 79 | 10/11/2021 | 05/10/2022 |
80 | Sample, 80 | 09/02/2014 | |
81 | Sample, 81 | 12/03/2012 | |
82 | Sample, 82 | 08/16/2010 | |
83 | Sample, 83 | 08/29/2016 | |
84 | Sample, 84 | 10/07/2019 | |
85 | Sample, 85 | 12/21/2018 | |
86 | Sample, 86 | 06/05/2013 | |
87 | Sample, 87 | 08/03/2009 | |
88 | Sample, 88 | 01/18/2021 | |
89 | Sample, 89 | 01/01/2019 | |
90 | Sample, 90 | 11/16/2020 | 02/09/2022 |
91 | Sample, 91 | 09/05/2019 | |
92 | Sample, 92 | 02/18/2019 | |
93 | Sample, 93 | 08/07/2000 | |
94 | Sample, 94 | 11/23/2020 | |
95 | Sample, 95 | 08/21/2017 | |
96 | Sample, 96 | 08/06/2018 | |
97 | Sample, 97 | 12/17/2018 | |
98 | Sample, 98 | 01/04/2016 | |
99 | Sample, 99 | 08/01/2002 | |
100 | Sample, 100 | 05/07/2018 | |
101 | Sample, 101 | 06/10/2019 | |
102 | Sample, 102 | 04/07/2019 | |
103 | Sample, 103 | 06/20/2017 | |
104 | Sample, 104 | 05/15/2017 | |
105 | Sample, 105 | 03/01/2017 | |
106 | Sample, 106 | 04/15/2019 | |
107 | Sample, 107 | 10/01/2018 | |
108 | Sample, 108 | 05/07/2018 | |
109 | Sample, 109 | 09/30/2019 | |
110 | Sample, 110 | 05/14/2021 | |
111 | Sample, 111 | 04/18/2019 |
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Hi @Nabarun1992,
Can you please share a pbix or some dummy data that keep the raw data structure with expected results? It should help us clarify your scenario and test to coding formula.
How to Get Your Question Answered Quickly
Regards,
Xiaoxin Sheng
If this post helps, please consider accept as solution to help other members find it more quickly.
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