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?"
Related
I am trying to come up with some arithmetic calculations for some survey data. I want to do these calculations for a number of segments and want to figure out how to do it without writing numerous SELECT statements.
This is what I have so far:
FACT table. This tables holds survey data at a respondent level - for example, if a survey had 10 questions, this table will have 11 columns: a column to identify the respondent_ID and 10 other columns to identify the responses to those questions.
DIMENSION table. This table segments we want to view the survey data by at a respondent level - for example, if we want to view survey responses by membership_status and age_bracket, this table will have 3 columns: a column to identify the respondent_ID, and two columns to identify membership_status and age_bracket.
OUTPUT.
I want to get aggregate calculations to summarizes the responses to the survey overall and to each question. I also want to be able to get this information for all possible segments that exist in the DIMENSIONS table.
I can do the query below, however I'll need to do this for every segment:
SELECT
COUNT(DISTINCT(CASE WHEN f.QUESTION_1 IN ('8', '9', '10') THEN f.RESPONDENT_ID END))*1.0 / COUNT(DISTINCT(CASE WHEN f.QUESTION_1 IS NOT NULL THEN f.RESPONDENT_ID END))*1.0 AS CSAT_1
FROM FACT f
JOIN DIMENSION d ON f.RESPONDENT_ID = d.RESPONDENT_ID
WHERE d.MEMBERSHIP_STATUS = 'ACTIVE'
The calculation above gives us something called a top 3 box. That is just one calculation, I will need to do many of them. Additionally, ever calculation will need to be done for each segment. In order to get a calculation for nonactive members, I would need to run another query and set d.MEMBERSHIP_STATUS = 'INACTIVE' and I would need to run another query with no filter, to get the overall calculation.
Is there a way I could store all my arithmetic calculations needed in my output as a function (maybe in a temp table or something) - my thought is that it'll be better to set the functions somewhere, and then when I need to calculate the output, I would some how call the function to do all the calculations I need, and give me all the calculations for every segment I have?
I can't fully envision how to get there, or if this is even a good solution, so guidance and detailed SQL code would be extremely helpful.Examples please!
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
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 have a query to pull clickthrough for a funnel, where if a user hit a page it records as "1", else NULL --
SELECT datestamp
,COUNT(visits) as Visits
,count([QE001]) as firstcount
,count([QE002]) as secondcount
,count([QE004]) as thirdcount
,count([QE006]) as finalcount
,user_type
,user_loc
FROM
dbname.dbo.loggingtable
GROUP BY user_type, user_loc
I want to have a column for each ratio, e.g. firstcount/Visits, secondcount/firstcount, etc. as well as a total (finalcount/Visits).
I know this can be done
in an Excel PivotTable by adding a "calculated field"
in SQL by grouping
in PowerPivot by adding a CalculatedColumn, e.g.
=IFERROR(QueryName[finalcount]/QueryName[Visits],0)
BUT I need give the report consumer the option of slicing by just user_type or just user_loc, etc, and excel will tend to ADD the proportions, which won't work b/c
SUM(A/B) != SUM(A)/SUM(B)
Is there a way in DAX/MDX/PowerPivot to add a calculated column/measure, so that it will be calculated as SUM(finalcount)/SUM(Visits), for any user-defined subset of the data (daterange, user type, location, etc.)?
Yes, via calculated measures. calculated columns are for creating values that you want to see on rows/columns/report header...calculated measures are for creating values that you want to see in the values section of a pivot table and can slice/dice by the columns in the model.
The easiest way would be to create 3 calculated "measures" in the calculation area of the powerpivot sheet.
TotalVisits:=SUM(QueryName[visits])
TotalFinalCount:=SUM(QueryName[finalcount])
TotalFinalCount2VisitsRatio:=[TotalFinalCount]/[TotalVisits]
You can then slice the calculated measure [TotalFinalCount2VisitsRatio] by user_type or just user_loc (or whatever) and the value will be calculated correctly. The difference here is that you are explicitly telling the xVelocity engine to SUM-then-DIVIDE. If you create the calculated column, then the engine thinks you want to DIVIDE-then-SUM.
Also, you don't have to break down the measure into 3 separate measures...it's just good practice. If you're interested in learning more, I'd recommend this book...the author is the PowerPivot/DAX guru and the book is very straightforward.
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).