I have volume data for specific customers. The customer names come from salesforce and the volume comes from another table. When I add each in tableau, i get a nice table that seems to be working.
We can see that there are 19 values ~500 My ultimate goal is to sum these based upon filters.
A way i discovered that i can do that is to use the syntax
{ FIXED [Account Id]: count([Volume]) }
But when i do that,
I get
When I change my function to count([volume]) i get a count of all joined rows ~250k
My question is how do i make this respect indivudal entries in the database and not all the joined values? If there was a way to do the sum for distinct timestamps in another field this would also work? Any other advice would be helpful from you tableau experts.
Thanks!
I think i got it. In the table of the database that i was trying to calculate there were 20 rows that needed to be calculated. When the data was joined in SF, it duplicated the rows. The trick here was to do the sum of the max for each primary key
SUM({ FIXED [Pk], [Name1] : MAX([Volume]) })
Related
Does anyone know if I can add two rows together so that I end up with just one row in Tableau (see screenshot)? So, if both rows are city Aachen and one row has a value for cost but not for purchasing power and the other row has a value for purchasing power but not cost, I would want just one row with both values. I am not interested in the columns "Table Name" and "Document Index(...". Thankful for any help!
Manipulating data like that in Tableau is usually no-go. Nevertheless, you can try Tableau prep and you should be able to do what you need here. Or maybe a different tool (even excel).
With that said, even though you have the info in two rows, the default approach for Tableau is always to aggregate data, so even if you have many rows with similar cases, once you take it to a viz using City (for example) as a dimension, this issue shouldn't really matter.
My dataset is two fixed income indices feeding into Tableau via one Excel document. Within the spreadsheet is a column containing "index A" or "index B" depending on which index the line item relates to. I need a way of finding the companies that appear in both indices, is anyone able to shed any light? Thank you
Assuming the company name is consistent (you're probably using a ticker so this shouldn't be a prob) you can do this with a simple LOD calc. All of those companies that have more than one unique entry in the Index column are in both indices. Try this and adapt for your data source:
{FIXED [Company]:COUNTD([Index])}
You can use this to isolate companies with both indices:
{FIXED [Company]:COUNTD([Index])}>1
Put that on the filters and set to True. It should exclude all companies in only 1 index.
I'm trying to create a Measure in Power BI using DAX that achieves the below.
The data set has four columns, Name, Month, Country and Value. I have duplicates so first I need to dedupe across all four columns, then group by Month and sum up the value. And then, I need to average across the Month to arrive at a single value. How would I achieve this in DAX?
I figured it out. Reply by #OscarLar was very close but nested SUMMARIZE causes problems because it cannot aggregate values calculated dynamically within the query itself (https://www.sqlbi.com/articles/nested-grouping-using-groupby-vs-summarize/).
I kept the inner SUMMARIZE from #OscarLar's answer changed the outer SUMMARIZE with a GROUPBY. Here's the code that worked.
AVERAGEX(GROUPBY(SUMMARIZE(Data, Data[Name], Data[Month], Data[Country], Data[Value]), Data[Month], "Month_Value", sumx(CURRENTGROUP(), Data[Value])), [Month_Value])
Not sure I completeley understood the question since you didn't provide example data or some DAX code you've already tried. Please do so next time.
I'm assuming parts of this can not (for reasons) be done using power query so that you have to use DAX. Then I think this will do what you described.
Create a temporary data table called Data_reduced in which duplicate rows have been removed.
Data_reduced =
SUMMARIZE(
'Data';
[Name];
[Month];
[Country];
[Value]
)
Then create the averaging measure like this
AveragePerMonth =
AVERAGEX(
SUMMARIZE(
'Data_reduced';
'Data_reduced'[Month];
"Sum_month"; SUM('Data_reduced'[Value])
);
[Sum_month]
)
Where Data is the name of the table.
I will try to explain the problem on an abstract level first:
I have X amount of data as input, which is always going to have a field DATE. Before, the dates that came as input (after some process) where put in a table as output. Now, I am asked to put both the input dates and any date between the minimun date received and one year from that moment. If there was originally no input for some day between this two dates, all fields must come with 0, or equivalent.
Example. I have two inputs. One with '18/03/2017' and other with '18/03/2018'. I now need to create output data for all the missing dates between '18/03/2017' and '18/04/2017'. So, output '19/03/2017' with every field to 0, and the same for the 20th and 21st and so on.
I know to do this programmatically, but on powercenter I do not. I've been told to do the following (which I have done, but I would like to know of a better method):
Get the minimun date, day0. Then, with an aggregator, create 365 fields, each has that "day0"+1, day0+2, and so on, to create an artificial year.
After that we do several transformations like sorting the dates, union between them, to get the data ready for a joiner. The idea of the joiner is to do an Full Outer Join between the original data, and the data that is going to have all fields to 0 and that we got from the previous aggregator.
Then a router picks with one of its groups the data that had actual dates (and fields without nulls) and other group where all fields are null, and then said fields are given a 0 to finally be written to a table.
I am wondering how can this be achieved by, for starters, removing the need to add 365 days to a date. If I were to do this same process for 10 years intead of one, the task gets ridicolous really quick.
I was wondering about an XOR type of operation, or some other function that would cut the number of steps that need to be done for what I (maybe wrongly) feel is a simple task. Currently I now need 5 steps just to know which dates are missing between two dates, a minimun and one year from that point.
I have tried to be as clear as posible but if I failed at any point please let me know!
Im not sure what the aggregator is supposed to do?
The same with the 'full outer' join? A normal join on a constant port is fine :) c
Can you calculate the needed number of 'dublicates' before the 'joiner'? In that case a lookup configured to return 'all rows' and a less-than-or-equal predicate can help make the mapping much more readable.
In any case You will need a helper table (or file) with a sequence of numbers between 1 and the number of potential dublicates (or more)
I use our time-dimension in the warehouse, which have one row per day from 1753-01-01 and 200000 next days, and a primary integer column with values from 1 and up ...
You've identified you know how to do this programmatically and to be fair this problem is more suited to that sort of solution... but that doesn't exclude powercenter by any means, just feed the 2 dates into a java transformation, apply some code to produce all dates between them and for a record to be output for each. Java transformation is ideal for record generation
You've identified you know how to do this programmatically and to be fair this problem is more suited to that sort of solution... but that doesn't exclude powercenter by any means, just feed the 2 dates into a java transformation, apply some code to produce all dates between them and for a record to be output for each. Java transformation is ideal for record generation
Ok... so you could override your source qualifier to achieve this in the selection query itself (am giving Oracle based example as its what I'm used to and I'm assuming your data in is from a table). I looked up the connect syntax here
SQL to generate a list of numbers from 1 to 100
SELECT (MIN(tablea.DATEFIELD) + levquery.n - 1) AS Port1 FROM tablea, (SELECT LEVEL n FROM DUAL CONNECT BY LEVEL <= 365) as levquery
(Check if the query works for you - haven't access to pc to test it at the minute)
How can I create a DAX query that retrieves rows from a given range in that order. Let's say I want the rows from row 1000 to row 2000. There is no unique id in my database. Should I add one, or is it possible without it?
If you can't distinguish a filter to create the subset of rows you are targeting then I would use a unique ID. I have not come across anything in DAX that allows to select rows in your powerpivot data set. If there isn't anything unique about the data you are targeting then I imagine you would need a unique ID.
i.e. I normally have column values I can filter with to target or create the subset of data I want to use.
I hope I am wrong and there is a way and look forward to someone posting a way.