I've been building an MDX query using excel's powerpivot. I connect to my cube, drag and drop Measures /Dimensions and my query has been working just fine. Up until I try to pull different dimensions.
A simple version of my query:
SELECT
NON EMPTY { [Measures].[EP Projected Impressions] } ON COLUMNS,
NON EMPTY { ([EP Hierarchy].[EP Tactic ID].[EP Tactic ID].ALLMEMBERS ) } ON ROWS
FROM [MI_Cube]
This will return:
(EP Tactic ID) (EP Projected Impressions)
1 10
2 20
3 30
4 40
5 50
Now when I try to pull in date information for each tactic from the Time dimension it just gives me a copy of the above results with each time dimension member.
Example query:
SELECT
NON EMPTY { [Measures].[EP Projected Impressions] } ON COLUMNS,
NON EMPTY { ([EP Hierarchy].[EP Tactic ID].[EP Tactic ID].ALLMEMBERS * [Time].[Fiscal Year].[Fiscal Year].ALLMEMBERS ) } ON ROWS
FROM [MI_Cube]
Results:
(EP Tactic ID) (EP Projected Impressions) (Fiscal Year)
1 10 FY2015
1 10 FY2014
1 10 FY2013
1 10 FY2012
1 10 FY2011
2 20 FY2015
2 20 FY2014
2 20 FY2013
2 20 FY2012
2 20 FY2011
etc....
Does this mean that I cannot pull the Time.FiscalYear dimension for each TacticID? Or do I need to restructure my query? EP Hierarchy has lots of dimension members I can pull successfully, but when I try to pull anything from EP Hierarchy and Time my results get multiplied instead of combined.
Thanks for any advice, trying to wrap my head around cubes and mdx queries.
It seems that you are simply missing a relation between the fact table holding the [EP Projected Impressions] member, and the dimension table holding your [Time] dimension.
By adding a relation between a foreign key on the fact table and the primary key on the dimension table, your measures should get correctly filtered by any attributes you slice on the dimension.
Thank you for the responses, it turns out the measure I was using was not connected to the time dimension. Apparently that was an expected behavior, after trying different measures I am getting the results I was expecting.
Related
I've got a large table of events that have occurred in an inventory of vehicles, which affect whether they are in service or out of service. I would like to create a measure that would be able to count the number of vehicles in the various inventories at any point in time, based on the events in this table.
This table is pulled from a SQL database into an Excel 2016 sheet, and I'm using PowerPivot to try to come up with the DAX measure.
Here is some example data event_list:
vehicle_id event_date event event_sequence inventory
100 2018-01-01 purchase 1 in-service
101 2018-01-01 purchase 1 in-service
102 2018-02-04 purchase 1 in-service
100 2018-02-07 maintenance 2 out-of-service
101 2018-02-14 damage 2 out-of-service
101 2018-02-18 repaired 3 in-service
100 2018-03-15 repaired 3 in-service
102 2018-05-01 damage 2 out-of-service
103 2018-06-03 purchase 1 in-service
I'd like to be able to create a pivot table in Excel (or use CUBE functions, etc) to get an output table like this:
date in-service out-of-service
2018-02-04 3 0
2018-02-14 1 2
2018-03-15 3 0
2018-06-03 3 1
Essentially, I want to be able to calculate the inventory based on any date in time. The example only has a few dates, but hopefully provides enough of a picture.
I've basically come up with this so far, but it counts more vehicles than desired - I can't figure out how to only take the latest event_sequence or event_date and use that to count the inventory.
cumulative_vehicles_at_date:=CALCULATE(
COUNTA([vehicle_id]),
IF(IF(HASONEVALUE (event_list[event_date]), VALUES (event_list[event_date]))>=event_list[event_date],event_list[event_date])
)
I tried using MAX() and EARLIER() functions, but they don't seem to work.
Edit: Added the PowerBI tag as I'm now using that software to attempt to solve this as well. See comments on Alexis Olson's answer.
I think I've found a much cleaner method than I gave previously.
Let's add two columns onto the event_list table. One which counts vehicles "in-service" on that date and one which counts vehicles "out-of-service" on that date.
InService =
VAR Summary = SUMMARIZE(
FILTER(event_list,
event_list[event_date] <= EARLIER(event_list[event_date])),
event_list[vehicle_id],
"MaxSeq", MAX(event_list[event_sequence]))
VAR Filtered = FILTER(event_list,
event_list[event_sequence] =
MAXX(
FILTER(Summary,
event_list[vehicle_id] = EARLIER(event_list[vehicle_id])),
[MaxSeq]))
RETURN SUMX(Filtered, 1 * (event_list[inventory] = "in-service"))
You can create an analogous calculated column for OutOfService or you can just take the total minus the InService count.
OutOfService =
CALCULATE(
DISTINCTCOUNT(event_list[vehicle_id]),
FILTER(event_list,
event_list[event_date] <= EARLIER(event_list[event_date])))
- event_list[InService]
Now all you have to do is put event_date on the matrix visual rows section and add the InService and OutOfService columns to the values section (use Maximum or Minimum for the aggregation option rather than Sum).
Here's the logic behind the calculated column InService:
We first create a Summary table which calculates the maximal event_sequence value for each vehicle. (We filter the event_date to only consider dates up to the current one we are working with.)
Now that we know what the last event_sequence value is for each vehicle, we use that to filter the entire table down to just the rows that correspond to those vehicles and sequence values. The filter goes through the table row by row and checks to see if the sequence value matches the one we calculated in the Summary table. Note that when we filter the Summary table to just the vehicle we are currently working with, we only get a single row. I'm just using MAXX to extract the [MaxSeq] value. (It's kind of like using LOOKUPVALUE, but you can't use that on a variable.)
Now that we've filtered the table just to the most recent events for each vehicle, all we need to do is count how many of them are "in-service". I used a SUMX here where the 1*(True/False) coerces the boolean value to return 1 or 0.
This is pretty difficult. I don't have a great answer, but here's something that kind of works.
You'll create a new calculated table where you'll calculate the status for each vehicle on each date. Start with the base cross join for each vehicle and each date:
= CROSSJOIN(VALUES(event_list[vehicle_id]), VALUES(event_list[event_date]))
Then add a calculated column to find the max sequence number for each vehicle on that date.
Sequence = MAXX(
FILTER(event_list,
event_list[event_date] <= Cross[event_date] &&
event_list[vehicle_id] = Cross[vehicle_id]),
event_list[event_sequence])
Now you can lookup the inventory value for each vehicle/sequence pair with another calculated column:
Inventory = LOOKUPVALUE(
event_list[inventory],
event_list[vehicle_id], Cross[vehicle_id],
event_list[event_sequence], Cross[Sequence])
The result should look something like this:
Once you have this, you can create a matrix using this calculated table. Put the event_date on the rows and Inventory on the columns. Filter out blank inventory values in the visual level filter and put the vehicle_id in the values field, using a count or distinct count as the aggregation method (instead of the default sum).
It should look like this:
I have a SSAS DSV similar to following structure:
Id Type Special
1 A 1
2 B Null
3 A Null
4 C 1
5 C Null
I built a dimension for this DSV including one attribute for Type.
Then I have in my cube three measures
Measure1: Count of rows
Measure2A: Sum of Special
Measure2B: Count of non-empty values for Special
Finally in Excel, I display data as following:
Rows --> Type attribute
Values --> Measure1 / Measure2A / Measure2B
When I look at the results, everything is correct.
For instance, I get a count of 1 for measure2A and measure 2B for row = C
BUT when I attempt to drill through for related cells, instead of getting 1 row, I get 2 (the ones where type = C without considering the value of Special)
I guess I am doing something wrong in my design of the cube but cannot understand what.
When determining what rows to show in drillthrough SSAS only considers the dimension context not which detail rows have a non null measure value.
You could add a new dimension on the Special column and add that dimension as a filter to your PivotTable.
Or you could install ASSP and construct a custom rowset action that fires an MDX query which does a NON EMPTY on your measure.
http://asstoredprocedures.codeplex.com/wikipage?title=Drillthrough&referringTitle=Home
What I want to do is generate a report containing an overview of gains and losses (of contracts). For example:
Year | contract_gains | contract_losses
_______________________________________
2015 | 10 | 2
2016 | 15 | 4
Showing the gains is quite easy because I can just count distinct contracts (which is the aggregator for the measure value) with a start period.
SELECT
{[contract_start_date].[year].MEMBERS}
ON ROWS,
{[Measures].[value]}
ON COLUMNS
FROM Cube
Showing the losses seperately is also easy because I can do the same with the second date dimension.
SELECT
{[contract_end_date].[year].MEMBERS}
ON ROWS,
{[Measures].[value]}
ON COLUMNS
FROM Cube
But what I want to do is generate a report containing both of the values in a single report. Sadly I have no idea how I can do this.
A little slow method, going cell by cell. Does this work for you -
WITH MEMBER [Measures].contract_losses AS
(
GENERATE
(
[contract_start_date].[year].CURRENTMEMBER,
FILTER
(
[contract_end_date].[year].MEMBERS,
CStr([contract_start_date].[year].CURRENTMEMBER.MEMBER_VALUE) = CStr([contract_end_date].[year].CURRENTMEMBER.MEMBER_VALUE)
)
).ITEM(0)
,
[Measures].[value]
)
MEMBER [Measures].contract_gains AS
[Measures].[value]
SELECT
NON EMPTY {[contract_start_date].[year].MEMBERS}
ON ROWS,
{[Measures].contract_gains, [Measures].contract_losses}
ON COLUMNS
FROM [Cube]
I have a Product dimension with hierarchies - product_id, initial_price, product_name and Measures - units_sold, cost_per_unit, revenue_per_unit. For each product_id I need to compare initial_price against revenue_per_unit and then assign it to a bucket based on the comparison.
Consider the following example:
Input:
product_id initial_price revenue_per_unit
1 10 12
2 20 18
3 30 30
Output:
product_id bucket_name
1 Profit
2 Loss
3 Same
How can I achieve this using MDX?
WITH Member [Measures].[Bucket] AS
CASE
WHEN [Measures].[initial_price] < [Measures].[revenue_per_unit] THEN
"Profit"
WHEN [Measures].[initial_price] > [Measures].[revenue_per_unit] THEN
"Loss"
ELSE
"Same"
END
SELECT {[Measures].[Bucket]}
ON COLUMNS,
[Product].[Product Name].Members
ON ROWS
FROM [yourcube]
should deliver what you want. Please note that calculated measures need not return numbers, they also can return strings in MDX (they even can return a string for some cells, and a number for others).
In case you do not have the price available as e. g. an average price on aggregated product level, and want to do the bucketing on product level, the best solution would be not do do that in MDX at all, but in the cube design: Just calculate the bucket on the relational side, and add it as an attribute to the product dimension.
You did not state anything about other dimensions, especially time. In case some other dimensions matter as well to determine the bucket, it might be necessary to add a separate dimension just for the buckets.
I need to filter the measure values as
MeasureA MeasureB
10 10
15 15
5 20
20 20
Here I need to get only the measures are not equal, I am using filter function as but not working
Select Filter({[Measures].[A],
[Measures].[B]},
([Measures].[A]-
[Measures].[B])=0)
on 0
from [Cube]
Expected result set
MeasureA MeasureB
5 20
What am I missing?
Try using a dimension instead of your measures for the first part of the filter statement. Assuming you are querying products then your query might look like:
select {[Measures].[A],[Measures].[B]} on columns,
filter ({[Products].Members},[Measures].[A] = [Measures].[B]) on rows
from [Sales Cube]
You might want to try creating a calculated field in the DSV for this Fact table...
CASE
WHEN MeasureFieldA != MeasureFieldB THEN 1
ELSE 0
END
Then you can create a "fact dimension" and have this calculated field as an attribute to be used in your queries or calculated measures.