I want the equivalent SUM and Group By as in t-SQL. But I haven't found the answer on the web.
My MDX return has some records that have the same name. I want to show the distinct name with the measure summed up just like Group by feature in SQL.
It seems like it's a common feature. Thanks.
When you define a measure in AS you can set it several different ways including count and sum.
Let's assume you have a product dimension and a fact of sales. A simple query to get the total sales by product would look like the following.
SELECT {[Measures].[ItemCount], [Measures].[SalesDollars]} ON 0,
[Products].[Products].children ON 1
FROM [CUBE]
This would give you sample output like
Product Item Count Sales Dollars
Bike 10 1000
Tire 3 650
Related
I’m having a problem trying to lock the aggregation level in a result.
I have a report showing : store, articule, sales, and stock. I need that the sales metric doesn’t change despite the store.
For example: if one articule had 3 sales in one store and 2 sales in the other one, the report should show 5 sales no matter what store I am looking for.
Do you have any suggestions?
You have to create a custom metric and use the BY ALL statement.
If the metric returning 3 and 2 looks like SELECT SUM(Sales), the metric returning 5 would be SELECT SUM(Sales) BY ALL Store.
I have the below table connected into Power BI and I am looking for ways to create a formula calculating % of grand total of the Rating column and further subtracting with targets for each rating. For example, the % of grand total for Rating 1 is 3 divided by 7 (42.86%). The most important part of the formula is the denominator which has to remain at a total level and dynamic for any filters applied to either Grade or BU columns. For example, denominator at a total level would be 7 and when filtered down to Academy BU should be 3.
Sample Data Table:
Rating Target Table:
I want the end result to look like this,
I have used the following formula to achieve this,
Measure created: % of total calc = DIVIDE(COUNT('Table'[Rating]),CALCULATE(SUM('Table'[Count]),'Table'[Rating]))
To make the above formula work I had to add an extra column and include ones in it (see below)
I want to know if there are other ways of achieving this outcome?
ALLEXCEPT will produce such result to exclude used dimensions and include mandatory filters such as date with one condition, rating, date, any dimension must be in the same table.
I am looking for a way to add up averages in SQL. Here is an example of the data I have:
product avg_price
phone 104.28
car 1000.00
And I'm looking to build something like this:
product avg_price
[all] 544.27
phone 104.28
car 1000.00
The way I'm currently doing it is to store the count and sum in two different columns, such as:
product cnt total
phone 203 20,304.32
car 404 304,323.30
And from that get the average. However, I was wondering if it is possible in SQL to just 'keep the fraction' and be able to add them as needed. For example:
product avg_price
[all] [add the fractions]
phone 20,304.32 / 203
car 304,323.30 / 404
Or do I need to use two columns in order to get an average of multiple aggregated rows?
You don't need 2 columns to get the average, but if you want to display as a fraction then you will need both numbers. They don't need to be in 2 columns though.
select product, sum(total) ||'/'||sum(count)
from table a
join table b on a.product=b.product
union
select product, total ||'/'||count
from table a
join table b on a.product=b.product;
I'm trying to understand how TOTAL and Aggr work in QlikView. Could someone please explain the difference between the two examples below, and if possible please illustrate with a SQL query?
Example1:
Max({<Field1=>} Aggr(Sum({<Field2={'Value'}, Field1=>} StuffCount), Field1))
Example2:
Max({<Field1=>} TOTAL Aggr(Sum({<Field2={'Value'}, Field1=>} StuffCount), Field1))
Not sure what you mean with and SQL query in this example. Anyway, imagine you have this list of Customers (CustomerID) and Sales (Sales):
CustomerID/ Sales
Customer1 25
Customer2 20
Customer1 10
Customer1 5
Customer1 20
Customer3 30
Customer2 30
Then you want to show it on a pivot table with dimension CustomerID and two expressions:
Max(Aggr(Sum(Sales), CustomerID)) // this will show 60 for the first customer, 50 for the second and 30 for the third one
Max(TOTAL Aggr(Sum(Sales),CustomerID)) //this will show 60 in every row of your table (which is the maximum sum of sales among all customers)
So basically AGGR creates a temporal list of whatever you put in the first function input (in this case sum(Sales)) using the dimension of the second (CustomerID). Then you can perform operations on that list (such as Max, Min, Avg...). If you write TOTAL and use the expression in a pivot table, then you 'ignore' the dimensions that might be affecting the operations.
Hope it helps
TOTAL keyword is useful in charts/pivot tables. It applies the same calculation on every datapoint in the chart/pivot, with independence of dimentions.
Therefore - if you put your expression into pivot table - 1st option may display different values per cell (if the Aggr is rellevant) when the 2nd will result in same values.
Aggr function allows making double aggregations (avg of sum, max of count etc..) on different group by bases.
I want the sum of a count IF the count is >=3. This gives me a sum of all the counts, regardless if they are <> 3:
=Sum(Iif(CountDistinct(Fields!ENCOUNTER.Value)>=3,1,0))
This produces th same result, the total number of distinct encounters:
=Sum(Iif(CountDistinct(Fields!ENCOUNTER.Value)>=3,CountDistinct(Fields!ENCOUNTER.Value),Nothing))
I want the total number of distinct encounters if there are 3 or more per person. I am grouping on person first, then encounter id.
Ex:
Person Enc
John 1
Bob 4
Sue 2
Ann 3
Total Enc>=3: 2
Based on your requirement, if there are not details rows under ENCOUNTER, you should directly compare the Fields!ENCOUNTER.Value instead of using countdistinct()
Sum(IIF(Fields!ENCOUNTER.value>=3,1,0))
If you have multiple detail rows under ENCOUNTER group level, your requirement can't be achieved because we can't use an aggregation function within an aggregation function. Which means we can't get the distinct ENCOUNTER IDs first, then calculate the total.
I found a workaround. I created another query that selects only those people with 3 or more encounters and added it to the report as a subreport