Im new (couple of days to be exact) on Cubes, I have the following problem.
I have a Measure that brings certain amount of data, 100 rows for example. From that data I want to filter numbers that are < 0 from one of its columns.
For example this measure:
[Measures].[Distribution CSU Groups]
Will bring data like this
enter image description here
As you can see in the link, I want to filter those rows that have negative values on the 3rd column.
Is it possible to do this via MDX and how?
Yes filtering is possible in mdx via the following functions:
IIF function
FILTER function
HAVING clause
Related
I have a problem with Tableau. In my worksheet I want to be able to use Sum(Field 1) to filter data I see on my sheet. So for example, If sum(sales)<20 only show the sales information which their sum is less than 20. When I try to create a calculated field to with the expression above Tableau converts it to a boolean filter instead of sliding my data to meet the filter criteria.
Is there any solution for the problem?
Thanks
you could filter the result using an having clause
select my_key, sum(field1)
from my_table
group by my_key
having sum(field1)<20
DAX 2013 standalone power pivot.
I have a sales table with Product and Brand columns, and Sales measure which explicitly sums up sales column.
Task in hand: I need to create 1 measure RANK which would ...
if Product is filtered expressly, then return count of Products that have higher or equal sales amount, divided by total count of products.
If it's a subtotal brand level, show the same but for brands.
My current approach is using RANK and then MAXX of rank which seems working but a no-go - slow nightmare. Excel runs out of memory.
Research: it's been a week. This is the most relevant post i found anywhere, this question here , but it's in MDX.
In my example picture, I'm showing Excel formulas with which I can get to the result. Ideally there shouldn't be any helpers, 1 formula for all.
I.E.
RANK:=IF( HASONEFILTER(PRODUCTS[PRODUCT], HELPER_PROD, HELPER_BRAND)
where HELPER_PROD part would be something like this - need to find a way to refer to "current" result in pivot table like Excel does using [#[...:
HELPER_PROD:=COUNTX(ALL(PRODUCTS), [SALES]>=[#[SALES]]) / COUNTX(ALL(PRODUCTS))
HELPER_BRAND:=COUNTX(
DISTINCT(ALL(PRODUCTS[BRAND])),
[SALES]>=[#[SALES]]) /
COUNT(DISTINCT(ALL(PRODUCTS[BRAND]))
You can use the "Earlier" function to compare with the current record.
ProductsWithHigherSales:=CALCULATE(countrows(sales),
FILTER(all(Sales),
countrows(filter(Sales,Sales[Sales]<=EARLIER(Sales[Sales])))
))
Using Earlier function in measures: can-earlier-be-used-in-dax-measures
Used workbook: Excel File
How to write this expression in PowerBI
select distinct([date]),Temperature from Device47A8F where Temperature>25
Totally new to PowerBI. Is there any tool that can change the query from sql to PowerBI expression?
I have tried so many type of different type of expressions but getting error, Most of the time I am getting this:
The expression refers to multiple columns. Multiple columns cannot be converted to a scalar value.
Need help, Thanks.
After I posted my answer, wondered if your expected result is get only one date by temperature, In other words, without repeated dates in your result set.
A side note: select distinct([date]),Temperature from Device47A8F where Temperature>25 returns repeated dates since DISTINCT keyword evaluate distinct columns values specified in the SELECT statement, it doesn't return distinct values in a specific column even if you surround it with parenthesis.
Now what brings us here. What I can see in your error is that you are trying to use a table-valued (produces a table with multiple columns) expression in a measure which only accepts scalar-valued (calculate only one value).
Supposing you have a table like this:
Running your SQL query you will get the highlighted in yellow rows:
You can see 01/09/2016 date is repeated. If you want to create a measure you have to define what calculation you want to show for temperature. i.e, average, max or min etc.
In the below expression is being calculated the maximum temperature greater than 25 per date:
MaxTempGreaterThan25 =
CALCULATE ( MAX ( Device47A8F[Temperature] ), Device47A8F[Temperature] > 25 )
In this case the measure MaxTempGreaterThan25 is calculated per date.
If you don't want to produce a measure but a table. In the Power BI Tool bar select Modeling tab and click New Table icon.
Use this expression:
MyTemperatureTable =
FILTER ( Device47A8F, Device47A8F[Temperature] > 25 )
It should produce a new table named MyTemperatureTable like this:
I recommend you learn some basics about DAX, it is pretty different from SQL / T-SQL and there are things you can't do depending on your model and data.
Let me know if this helps.
You probably don't need to write any code if your objective is to show the result in a Power BI visual e.g. a table. Power BI naturally aggregates data if the datatype is numeric (e.g. Temperature).
I would just add a Table visual on a Report page and add the Date and Temperature columns to it. Then in Visualizations / Fields / Values I would click the little down-arrow on the Temperature field and set the Aggregation e.g. Maximum. Then in Visualizations / Fields / Filters I would click the little down-arrow on the Temperature field and set the Filter e.g. is greater than: 25
Hard-coded solutions are unlikely to survive the next question from your users e.g. "but what if I want to see Temperature > 24? Or 20? Or 30?"
I'm building a cube in MS BIDS. I need to create a calculated measure that returns the weighted-average of the rank value weighted by the number of searches. I want this value to be calculated at any level, no matter what dimensions have been applied to break-down the data.
I am trying to do something like the following:
I have one measure called [Rank Search Product] which I want to apply at the lowest level possible and then sum all values of it
IIf([Measures].[Searches] IS NOT NULL, [Measures].[Rank] * [Measures].[Searches], NULL)
And then my weighted average measure uses this:
IIf([Measures].[Rank Search Product] IS NOT NULL AND SUM([Measures].[Searches]) <> 0,
SUM([Measures].[Rank Search Product]) / SUM([Measures].[Searches]),
NULL)
I'm totally new to writing MDX queries and so this is all very confusing to me. The calculation should be
([Rank][0]*[Searches][0] + [Rank][1]*[Searches][1] + [Rank][2]*[Searches][2] ...)
/ SUM([searches])
I've also tried to follow what is explained in this link http://sqlblog.com/blogs/mosha/archive/2005/02/13/performance-of-aggregating-data-from-lower-levels-in-mdx.aspx
Currently loading my data into a pivot table in Excel is return #VALUE! for all calculations of my custom measures.
Please halp!
First of all, you would need an intermediate measure, lets say Rank times Searches, in the cube. The most efficient way to implement this would be to calculate it when processing the measure group. You would extend your fact table by a column e. g. in a view or add a named calculation in the data source view. The SQL expression for this column would be something like Searches * Rank. In the cube definition, you would set the aggregation function of this measure to Sum and make it invisible. Then just define your weighted average as
[Measures].[Rank times Searches] / [Measures].[Searches]
or, to avoid irritating results for zero/null values of searches:
IIf([Measures].[Searches] <> 0, [Measures].[Rank times Searches] / [Measures].[Searches], NULL)
Since Analysis Services 2012 SP1, you can abbreviate the latter to
Divide([Measures].[Rank times Searches], [Measures].[Searches], NULL)
Then the MDX engine will apply everything automatically across all dimensions for you.
In the second expression, the <> 0 test includes a <> null test, as in numerical contexts, NULL is evaluated as zero by MDX - in contrast to SQL.
Finally, as I interpret the link you have in your question, you could leave your measure Rank times Searches on SQL/Data Source View level to be anything, maybe just 0 or null, and would then add the following to your calculation script:
({[Measures].[Rank times Searches]}, Leaves()) = [Measures].[Rank] * [Measures].[Searches];
From my point of view, this solution is not as clear as to directly calculate the value as described above. I would also think it could be slower, at least if you use aggregations for some partitions in your cube.
I'm working on SSRS report builder that is using a dataset calling a SQL Server 2000 database.
The query is getting sums of a few different fields and is also pulling out all records that have to do with that client number. I want to get the sum of the sum but it is way over because of the detail rows. Basically what I want is the sum of the distinct sum column values.
=Sum(Fields!tot.Value, "table1_Group3")
I saw that you can get sums by the groups and I tried the expression above but it comes back with an error:
The Value expression for the textbox 'tot' has a scope parameter that is not
valid for an aggregate function...
table1_Group3 is the name of the group that holds the sum value in the report.
Any suggestions on how to get the distinct values to sum them in this report.
=Sum(Fields!tot.Value, "table1_Group3")
The code above will give you the sum of "tot" for all rows in the current "table1_Group3." This means that this expression only makes sense somewhere within table1_Group3. Otherwise, SSRS doesn't know which is the current instance of that group.
Sounds like you would like to sum this value across multiple groups, but only take one "tot" from each instance of the group. (Are you sure that all rows in that group will have the same "Tot?")
If tot is the total of other fields in your returned data, then simply add those up in your formula. This may have the added benefit of simplifying your SQL query as well.
Some other options that could work:
- Change your SQL query so that only one row per group gets the Tot field set.
- Use Embedded code in the report to keep a running total which is added to only once per group, such as in the group header.
(If upgrading to 2008R2 SSRS is an option, then the Lookup function could be used here, maybe even to look back at the same dataset.)
change the query/ dataset to sum(distinct tot) using the temp table on the sql server
I suppose you need to write sum(distinct columnName).