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.
My problem:
I work for a company that sells stuff denoted by item numbers. I have these item numbers in a table. These item numbers also have various attributes assigned to them. We have several different sub companies that have the same item number and attributes. I'm trying to find a way to find any item attribute that does not match the others by sub company so we can do data clean up. Please see an example item:
ITEMNMBR | ITMCLSCD | Company | Brand | ATTRIBUTE_A | ATTRIBUTE_C | ATTRIBUTE_D | ATTRIBUTE_E | ATTRIBUTE_F | ATTRIBUTE_G | Material |
BTA4610 | BTA IMP | BHI | BIO | Premium | Shallow Conical Hex | Tapered Pro | Laser Lok | Mountfree | Human use implant (sterile) | Titanium alloy |
BTA4610 | BTA IMP | CHILE | BIO | Premium | Shallow Conical Hex | Tapered Pro | Laser Lok | Mountfree | Human use implant (sterile) | Titanium alloy |
BTA4610 | BTA IMP | ITA16 | BIO | Premium | Shallow Conical Hex | Tapered Pro | Laser Lok | Mountfree | Human use implant (sterile) | Titanium alloy |
BTA4610 | BTA IMP | GERM | BIO | Premium | Shallow Conical Hex | Tapered Pro | Laser Lok | Mountfree | Human use implant (sterile) | Titanium alloy |
BTA4610 | BTA IMP | UKING | BIO | Premium | Conical Hex | Tapered Pro | Laser Lok | Mountfree | Human use implant (sterile) | Titanium alloy |
BTA4610 | BTA IMP | CAN | BIO | Premium | Shallow Conical Hex | Tapered Pro | Laser Lok | Mountfree | Human use implant (sterile) | Titanium alloy |
BTA4610 | BTA IMP | IBER | BIO | Premium | Shallow Conical Hex | Tapered Pro | Laser Lok | Mountfree | Human use implant (sterile) | Titanium alloy |
The different attribute denotation is bolded and italicized.
I'm trying to make a flag or filter that picks these item attributes out.
My boss uses Access and can do this fairly easily using queries and pivot tables in excel. How can I do this in Power BI?
Hi @jguy
Try measure as:
Measure =
CALCULATE(
COUNTROWS('Table'),
FILTER(
ALL('Table'),
'Table'[ATTRIBUTE_A]=MAX('Table'[ATTRIBUTE_A]) &&
'Table'[ATTRIBUTE_C]=MAX('Table'[ATTRIBUTE_C]) &&
'Table'[ATTRIBUTE_D]==MAX('Table'[ATTRIBUTE_D]) &&
'Table'[ATTRIBUTE_E]=MAX('Table'[ATTRIBUTE_E]) &&
'Table'[ATTRIBUTE_F]=MAX('Table'[ATTRIBUTE_F]) &&
'Table'[ATTRIBUTE_G]=MAX('Table'[ATTRIBUTE_G])
)
)
Here is the output:
The pbix file is attached.
Best Regards,
Link
If this post helps then please consider Accept it as the solution to help the other members find it more quickly.
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 |
---|---|
105 | |
94 | |
75 | |
63 | |
62 |
User | Count |
---|---|
137 | |
105 | |
104 | |
80 | |
63 |