Values in different column to list in one using slicer(for filter) , Unpivot or other option.

[Aria_Nep]

Hello, I have connected the kobo tool box to power Bi and received the datas of indicators in different column, while making power Bi Dashboard I need a slicer (for filter purpose) , I did that by unpivoting however using this i got the the indicators from different column in one but the values associated with indicators (achievement , target, age wise data)  are duplicated or multiplied. I need the values without duplication. There are around 20 indicatos which i receive on power bi in different column, for example i have mention only 3 indicator below. I need help so that I can use the slicer(for filter purpose) to chose the indicators and change the value as per actual without duplication. I have also attached the desired dashboard screenshot. Help is apreciated. Thank you

Partners	Reporting Year	Reporting Quarter	1.1.1 Indicator Information/Select Indicator	1.1.1 Indicator Information/Total target	1.1.1 Indicator Information/Achievement of this reporting quarter	1.2.1 Indicator Information/Select Indicator	1.2.1 Indicator Information/Total target	1.2.1 Indicator Information/Achievement of this reporting quarter	1.2.1 Indicator Information/Child, Male (below than 18 years)	1.2.1 Indicator Information/Chid Female (Below than 18 years)	1.2.1 Indicator Information/Other below 18 years	1.2.1 Indicator Information/Male, aged between 18-25 years	1.2.1 Indicator Information/Female, aged between 18-25 years	1.2.1 Indicator Information/Other, aged between 18-25 years	1.2.1 Indicator Information/Male above than 25 years old	1.2.1 Indicator Information/Female above than 25 years old	1.2.1 Indicator Information/Other above than 25 years	1.2.2 Indicator Information/Select Indicator	1.2.2 Indicator Information/Total target	1.2.2 Indicator Information/Achievement of this reporting quarter	1.2.2 Indicator Information/Child, Male (below than 18 years)	1.2.2 Indicator Information/Chid Female (Below than 18 years)	1.2.2 Indicator Information/Other below 18 years	1.2.2 Indicator Information/Male, aged between 18-25 years	1.2.2 Indicator Information/Female, aged between 18-25 years	1.2.2 Indicator Information/Other, aged between 18-25 years	1.2.2 Indicator Information/Male above than 25 years old	1.2.2 Indicator Information/Female above than 25 years old	1.2.2 Indicator Information/Other above than 25 years
A	2023	Q4	1.1.1: Number of learning platform created	22	12	1.2.1: Number of people who beefited from learning platform	34	23	1	1	2	3	4	5	6	7	2	1.2.2: Number of advocacy of learning platform	3	4
J	2023	Q1	1.1.1: Number of learning platform created	2	5	1.2.1: Number of people who beefited from learning platform	3	2	1	2	3	4	5	6	7	8	1	1.2.2: Number of advocacy of learning platform	43	23	1	1	1	2	3	4	4	5	6
S	2025	Q3	1.1.1: Number of learning platform created	4	4	1.2.1: Number of people who beefited from learning platform	4	5	4	5	4	5	4	5	4	5	4	1.2.2: Number of advocacy of learning platform	4	5	4	5	4	5	4	5	4	4	5
R	2027	Q4	1.1.1: Number of learning platform created	10	5	1.2.1: Number of people who beefited from learning platform	50	2	100	123	234	124	12	134	123	90	8	1.2.2: Number of advocacy of learning platform	2	0	500	200	134	132	567	70	0	0	0
JV	2026	Q4	1.1.1: Number of learning platform created	5	5	1.2.1: Number of people who beefited from learning platform	5	4	5	4	5	4	5	4	5	4	4	1.2.2: Number of advocacy of learning platform	5	4	4	4	4	5	4	4	4	4	4
A	2023	Q1	1.1.1: Number of learning platform created	7	6	1.2.1: Number of people who beefited from learning platform	10	9	1	1	1	2	2	2	1	2	0	1.2.2: Number of advocacy of learning platform	5	4	1	1	0	1	2	0	1	2	0
S	2027	Q2	1.1.1: Number of learning platform created	5	4	1.2.1: Number of people who beefited from learning platform	5	4	4	4	5	4	5	4	5	4	5	1.2.2: Number of advocacy of learning platform	5	4	5	4	4	4	5	4	5	4	5
S	2026	Q3	1.1.1: Number of learning platform created	40	30	1.2.1: Number of people who beefited from learning platform	3	1	200	0	0	10	90	0	97	59		1.2.2: Number of advocacy of learning platform	3	1	35	598	0	78	65	0	78	98	0
J	2024	Q2	1.1.1: Number of learning platform created	6	5	1.2.1: Number of people who beefited from learning platform	7	6	1	1	0	1	1	0	2	0	0	1.2.2: Number of advocacy of learning platform	2	2	0	0	0	1	1	0	0	0	0
R	2025	Q3	1.1.1: Number of learning platform created	4	4	1.2.1: Number of people who beefited from learning platform	5	4	4	5	4	5	4	5	4	5	4	1.2.2: Number of advocacy of learning platform	4	5	4	5	4	5	4	5	4	5	4

[johnbasha33]

Clean up your dataset in Power Query. @Aria_Nep 

[Anonymous]

Hi @Aria_Nep ,
Based on your description, when you cancel the column pivot in Power BI, you are converting columns to rows. The process should not inherently duplicate data unless the operation contains more columns than necessary or is applied more than once.
Before applying the cancel pivot transformation, make sure that the dataset does not contain duplicate rows. If duplicate rows exist, they will be exacerbated during the unpivot process. You can use the Remove Duplicate Rows feature in the Power Query editor to clean up the data.
Working with duplicate values - Power Query | Microsoft Learn

Best regards,

Albert He

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