Comparison Chart

[Kishore_2912]

Hello,

Am a new one to powerbi dessktop. My requrement is, I want to compare the measurement values based on plant by selecting characteristic_name_and_id as a filter. Here mainly i want to differentiate which plant has higher measurement value when compared to other plant, same goes for lower value as well. Also i have added language filter in my page so that i can always check for 1 language because the other language also has same value
here is my sample data

product_area

part_no

inspection_plan_no

inspection_station

order_no

plant

production_unit

amk_id

status

date

time

USL

LSL

UWL

LWL

mw_messwert

unit

description_operation

stamp_no

language

characteristic_name_and_id

gb

mw_am_ts

measurement_server

characteristic_prod_unit

date_text

OperationKey

Interval

IPB2.0/DPB

1265.149.194

__P_25_00024

BhP_MFP_W670_IPB2.0_Loop_A1

BhP__P_25_00084

BhP

Loop A1

40294

ok

########

28:01.5

0.45

0.25

0.4

0.3

0.384

mm

Serienprüfung Tag

301

de

AGR 301 Staking_D_24978

VM

2026-05-05T12:28:01.487Z

DB_VM_BABTEC_PROD_SQL

AGR 301 Staking_D_24978-Loop A1

########

DAILY

Variabel

IPB2.0/DPB

1265.149.194

__P_25_00024

BhP_MFP_W670_IPB2.0_Loop_A1

BhP__P_25_00084

BhP

Loop A1

40294

ok

########

25:16.4

0.45

0.25

0.4

0.3

0.408

mm

Serienprüfung Tag

301

de

AGR 301 Staking_D_24978

VM

2026-04-16T14:25:16.413Z

DB_VM_BABTEC_PROD_SQL

AGR 301 Staking_D_24978-Loop A1

########

DAILY

Variabel

IPB2.0/DPB

1265.149.206

__P_25_00021

BhP_MFP_W670_IPB2.0_Loop_A1

BhP__P_25_00085

BhP

Loop A1

41472

ok

########

34:20.5

0.45

0.25

0.4

0.3

0.377

mm

Serienprüfung Tag

301

de

AGR 301 Staking_B_24757

VM

2026-04-20T14:34:20.487Z

DB_VM_BABTEC_PROD_SQL

AGR 301 Staking_B_24757-Loop A1

########

DAILY

Variabel

null

Variante 1_BhP

_IPB1.0_P_26_00003

PC Kiesel,Florian [Englisch]

Variante 1_BhP

BhP

Linie 1 [Englisch]

41720

ok

########

18:37.9

0.45

0.25

0.4

0.3

0.364

mm

Series Inspection Daily

301

en

AGR 301 Staking_B_28044

VM

2026-04-21T14:18:37.863Z

DB_VM_BABTEC_PROD_SQL

AGR 301 Staking_B_28044-Linie 1 [Englisch]

########

DAILY

Variable

null

Variante 1_TgP

__P_26_00007

PC Kiesel,Florian [Chinesisch]

Variante 1_TgP

TgP

Pfiffner CDD 2

40209

ok

########

00:20.8

0.45

0.25

0.4

0.3

0.38

mm

Serienprüfung Tag [Chinesisch]

301

zh

AGR 301 Staking_B_28098

VM

2026-03-20T11:00:20.817Z

DB_VM_BABTEC_PROD_SQL

AGR 301 Staking_B_28098-Pfiffner CDD 2

########

DAILY

变量

null

Variante 5_BhP

_IPB1.0_P_26_00003

PC Kiesel,Florian

Variante 5_IP_BhP

BhP

Linie 1

41994

ok

########

26:46.2

0.45

0.25

0.4

0.3

0.353

mm

Serienprüfung Schicht

301

de

AGR 301 Staking_A_30426

VM

2026-04-27T14:26:46.227Z

DB_VM_BABTEC_PROD_SQL

AGR 301 Staking_A_30426-Linie 1

########

SHIFT

Variabel

null

Variante 1_TgP

__P_26_00007

PC Kiesel,Florian

Variante 1_TgP

TgP

Pfiffner CDD 2

40210

ok

########

00:21.0

0.45

0.25

0.4

0.3

0.393

mm

Serienprüfung Tag

301

de

AGR 301 Staking_C_28099

VM

2026-03-20T11:00:20.960Z

DB_VM_BABTEC_PROD_SQL

AGR 301 Staking_C_28099-Pfiffner CDD 2

########

DAILY

Variabel

IPB2.0/DPB

1265.149.228

__P_25_00035

BhP_MFP_W670_IPB2.0_Loop_A1

BhP__P_25_00083

BhP

环路A1

38689

ok

########

49:42.8

0.45

0.25

0.4

0.3

0.419

mm

Serienprüfung Tag [Chinesisch]

301

zh

AGR 301 Staking_C_25682

VM

2026-02-11T10:49:42.770Z

DB_VM_BABTEC_PROD_SQL

AGR 301 Staking_C_25682-环路A1

########

DAILY

变量

IPB2.0/DPB

1265.149.228

__P_25_00035

BhP_MFP_W670_IPB2.0_Loop_A1

BhP__P_25_00083

BhP

Loop A1

38689

ok

########

15:02.5

0.45

0.25

0.4

0.3

0.398

mm

Serienprüfung Tag

301

de

AGR 301 Staking_C_25682

VM

2026-02-05T10:15:02.500Z

DB_VM_BABTEC_PROD_SQL

AGR 301 Staking_C_25682-Loop A1

########

DAILY

Variabel

IPB2.0/DPB

1265.149.228

__P_25_00035

BhP_MFP_W670_IPB2.0_Loop_A1

BhP__P_25_00083

BhP

环路A1

38689

ok

########

17:38.0

0.45

0.25

0.4

0.3

0.404

mm

Serienprüfung Tag [Chinesisch]

301

zh

AGR 301 Staking_C_25682

VM

2026-03-30T11:17:37.973Z

DB_VM_BABTEC_PROD_SQL

AGR 301 Staking_C_25682-环路A1

########

DAILY

变量

IPB2.0/DPB

1265.149.228

__P_25_00035

BhP_MFP_W670_IPB2.0_Loop_A1

BhP__P_25_00083

BhP

环路A1

38689

ok

########

15:02.5

0.45

0.25

0.4

0.3

0.398

mm

Serienprüfung Tag [Chinesisch]

301

zh

AGR 301 Staking_C_25682

VM

2026-02-05T10:15:02.500Z

DB_VM_BABTEC_PROD_SQL

AGR 301 Staking_C_25682-环路A1

########

DAILY

变量

IPB2.0/DPB

1265.149.228

__P_25_00035

BhP_MFP_W670_IPB2.0_Loop_A1

BhP__P_25_00083

BhP

环路A1

38689

ok

########

46:09.8

0.45

0.25

0.4

0.3

0.4

mm

Serienprüfung Tag [Chinesisch]

301

zh

AGR 301 Staking_C_25682

VM

2026-02-16T09:46:09.767Z

DB_VM_BABTEC_PROD_SQL

AGR 301 Staking_C_25682-环路A1

########

DAILY

变量

IPB2.0/DPB

1265.149.228

__P_25_00035

BhP_MFP_W670_IPB2.0_Loop_A1

BhP__P_25_00083

BhP

Loop A1

38689

ok

########

40:19.5

0.45

0.25

0.4

0.3

0.382

mm

Serienprüfung Tag

301

de

AGR 301 Staking_C_25682

VM

2026-03-26T09:40:19.527Z

DB_VM_BABTEC_PROD_SQL

AGR 301 Staking_C_25682-Loop A1

########

DAILY

Variabel

IPB2.0/DPB

1265.149.228

__P_25_00035

BhP_MFP_W670_IPB2.0_Loop_A1

BhP__P_25_00083

BhP

Loop A1

38689

ok

########

40:19.5

0.45

0.25

0.4

0.3

0.382

mm

Series Inspection Daily

301

en

AGR 301 Staking_C_25682

VM

2026-03-26T09:40:19.527Z

DB_VM_BABTEC_PROD_SQL

AGR 301 Staking_C_25682-Loop A1

########

DAILY

Variable

IPB2.0/DPB

1265.149.228

__P_25_00035

BhP_MFP_W670_IPB2.0_Loop_A1

BhP__P_25_00083

BhP

Loop A1

38689

ok

########

50:22.7

0.45

0.25

0.4

0.3

0.393

mm

Series Inspection Daily

301

en

AGR 301 Staking_C_25682

VM

2026-02-03T09:50:22.733Z

DB_VM_BABTEC_PROD_SQL

AGR 301 Staking_C_25682-Loop A1

########

DAILY

Variable

IPB2.0/DPB

1265.149.228

__P_25_00035

BhP_MFP_W670_IPB2.0_Loop_A1

BhP__P_25_00083

BhP

环路A1

38689

ok

########

36:02.6

0.45

0.25

0.4

0.3

0.401

mm

Serienprüfung Tag [Chinesisch]

301

zh

AGR 301 Staking_C_25682

VM

2026-05-27T11:36:02.647Z

DB_VM_BABTEC_PROD_SQL

AGR 301 Staking_C_25682-环路A1

########

DAILY

变量

null

Variante 5_BhP

_IPB1.0_P_26_00003

PC Kiesel,Florian [Chinesisch]

Variante 5_IP_BhP

BhP

Linie 1 [Chinesisch]

41995

ok

########

06:45.4

0.45

0.25

0.4

0.3

0.38

mm

Serienprüfung Schicht [Chinesisch]

301

zh

AGR 301 Staking_B_30427

VM

2026-04-24T14:06:45.387Z

DB_VM_BABTEC_PROD_SQL

AGR 301 Staking_B_30427-Linie 1 [Chinesisch]

########

SHIFT

变量

null

Variante 5_BhP

_IPB1.0_P_26_00003

PC Kiesel,Florian [Englisch]

Variante 5_IP_BhP

BhP

Linie 1 [Englisch]

41995

ok

########

48:05.5

0.45

0.25

0.4

0.3

0.364

mm

Series Inspection Shift

301

en

AGR 301 Staking_B_30427

VM

2026-04-27T12:48:05.503Z

DB_VM_BABTEC_PROD_SQL

AGR 301 Staking_B_30427-Linie 1 [Englisch]

########

SHIFT

Variable

null

Variante 1_BhP

_IPB1.0_P_26_00003

PC Kiesel,Florian

Variante 1_BhP

BhP

Linie 1

41791

ok

########

52:48.9

0.45

0.25

0.4

0.3

0.38

mm

Serienprüfung Tag

301

de

AGR 301 Staking_D_28046

VM

2026-04-23T07:52:48.867Z

DB_VM_BABTEC_PROD_SQL

AGR 301 Staking_D_28046-Linie 1

########

DAILY

Variabel

null

Variante 1_BhP

_IPB1.0_P_26_00003

PC Kiesel,Florian [Englisch]

Variante 1_BhP

BhP

Linie 1 [Englisch]

41791

ok

########

45:34.7

0.45

0.25

0.4

0.3

0.38

mm

Series Inspection Daily

301

en

AGR 301 Staking_D_28046

VM

2026-04-23T07:45:34.757Z

DB_VM_BABTEC_PROD_SQL

AGR 301 Staking_D_28046-Linie 1 [Englisch]

########

DAILY

Variable

Could anyone guide me here

[Prince0011]

Yes, this is a good use case for Power BI. Based on your requirement, you want to:

• Filter by Characteristic_Name_And_ID.

• Filter by Language (so you only compare one language at a time).

• Compare the measurement value (mw_messwert) across different Plants.

• Easily identify which plant has the highest and lowest measurement values.

Recommended approach

1. Add slicers

Create two slicers:

• Characteristic_Name_And_ID

• Language

This will filter all visuals to the selected characteristic and language.

2. Create a measure for the measurement value

If each plant has multiple measurements, decide whether you want to compare the Average, Maximum, or Latest value.

For example, using the average:

Average Measurement =
AVERAGE('YourTable'[mw_messwert])

3. Create a Clustered Column Chart

Configure the visual as:

• X-axis: Plant

• Y-axis: Average Measurement

After selecting a characteristic, you'll immediately see which plant has the higher or lower value.

4. Highlight the highest and lowest plants

You can use conditional formatting with a color measure:

Plant Color =
VAR MaxValue =
    MAXX(ALLSELECTED('YourTable'[plant]), [Average Measurement])
VAR MinValue =
    MINX(ALLSELECTED('YourTable'[plant]), [Average Measurement])

RETURN
SWITCH(
    TRUE(),
    [Average Measurement] = MaxValue, "#00B050",   -- Green (Highest)
    [Average Measurement] = MinValue, "#FF0000",   -- Red (Lowest)
    "#5B9BD5"                                      -- Blue (Others)
)

Then apply this measure using Data colors → Conditional formatting (fx).

5. Add a Matrix for detailed comparison

A matrix can provide more context:

• Rows: Plant

• Columns: Characteristic_Name_And_ID (optional)

• Values:

  • Average Measurement

  • Min Measurement

  • Max Measurement

  • Standard Deviation (optional)

6. If you want to compare the latest measurement only

Instead of averaging all values, create a measure that returns the most recent measurement based on your date/time columns. This ensures you're comparing the latest inspection result for each plant.

Suggested report layout

+------------------------------------------------+
| Characteristic Slicer | Language Slicer         |
+------------------------------------------------+
| Clustered Column Chart (Plant vs Measurement)   |
+------------------------------------------------+
| KPI: Highest Plant | KPI: Lowest Plant          |
+------------------------------------------------+
| Matrix with detailed statistics by Plant        |
+------------------------------------------------+

If you're comparing measurements against USL (Upper Specification Limit) and LSL (Lower Specification Limit), you could also consider a Scatter Chart or Control/SPC Chart to visualize how each plant performs relative to the specification limits.

💡 Helpful? Give a Kudos 👍 — keep the community growing.

✅ Solved your issue? Mark this as the Accepted Solution ✔️

Best regards, Prince Singh | Data Science & Microsoft Fabric Enthusiast

[Ritaf1983]

Hi @Kishore_2912 

The requirement is not completely clear.

In general, you first need to create a measure that represents the value by which the plants should be compared. This could be an average, minimum, maximum, latest value, or another calculation depending on the business requirement. Simply summing the measurement values may not be appropriate, especially if the plants contain different numbers of measurements.

For the visual, a horizontal bar chart would probably be the clearest option:

* Plant on the Y-axis
* Measurement measure on the X-axis

You can then sort the chart by the measure to identify the plants with the highest and lowest values.

The language slicer should preferably be configured as single-select, since the different language rows appear to contain the same measurement values.

To provide a more specific solution, please clarify:

* Which calculation should be compared between plants: average, maximum, minimum, latest measurement, or something else?
* What result are you currently getting?
* Where exactly are you getting stuck?

If this post helps, then please consider Accepting it as the solution to help the other members find it more quickly.

[Kishore_2912]

Thanks. I would like to how did you create your bar chart i want the same like how you have created. When I try to create it is showing different

Could you explain in detail how you have achieved it?