MDX filter on fixed value depending on hierarcy level - ssas

I need to build a named set with mdx which tells me for a whole year what which are the large records. I cannot share my data, so I'll use a sales example.
All sales reps. need to enter their sales numbers in a application and on top of that database there is a cube configured. One of the goals is to find weird sales behaviour in this cube. This would mean a sales rep that is selling 100k every year, suddenly only sells 30k a year.
I have created a dynamic set that allows me to filter on this by using a calculated member named 'qualifies'. This qualifies is defined like this. (Diff is calculated before)
CREATE MEMBER Currentcube.qualifies AS iif(abs([Diff]) > 50000, 1, NULL),DISPLAY_FOLDER = 'Check big difference';
So this check can be used to filter all the sales reps that have a difference of 50k sales.
When I add aonther filter to my cube, for example region, the 50k threshold will never be exceeded, because no body has more than 50k sales in one region. I want to make the 50K dynamic based on my where clause in my filter.
My question is, is this possible? I'm fairly new to MDX so if this is an easy question, please forgive me. I have been trying lots of different scenario's but none gave a wanted result. I have been looking online, but this specific scenario hasn't passed in my search results.

Related

How to populate all possible combination of values in columns, using Spark/normal SQL

I have a scenario, where my original dataset looks like below
Data:
Country,Commodity,Year,Type,Amount
US,Vegetable,2010,Harvested,2.44
US,Vegetable,2010,Yield,15.8
US,Vegetable,2010,Production,6.48
US,Vegetable,2011,Harvested,6
US,Vegetable,2011,Yield,18
US,Vegetable,2011,Production,3
Argentina,Vegetable,2010,Harvested,15.2
Argentina,Vegetable,2010,Yield,40.5
Argentina,Vegetable,2010,Production,2.66
Argentina,Vegetable,2011,Harvested,15.2
Argentina,Vegetable,2011,Yield,40.5
Argentina,Vegetable,2011,Production,2.66
Bhutan,Vegetable,2010,Harvested,7
Bhutan,Vegetable,2010,Yield,35
Bhutan,Vegetable,2010,Production,5
Bhutan,Vegetable,2011,Harvested,2
Bhutan,Vegetable,2011,Yield,6
Bhutan,Vegetable,2011,Production,3
Image of the above csv:
Now there is a very small country lookup table which has all possible countries the source data can come with, listed. PFB:
I want to have the output data's number of columns always fixed (this is to ensure the reporting/visualization tool doesn't get dynamic number columns with every day's new source data ingestions depending on the varying distinct number of countries present).
So, I've to somehow join the source data with the country_lookup csv and populate all those columns with default value as F. Every country column would be binary with T or F being the possible values.
The original dataset from the above has to be converted into below:
Data (I've kept the Amount field unsolved for column Type having Derived Yield as is, rather than calculating them below for a better understanding and for you to match with the formulae):
Country,Commodity,Year,Type,Amount,US,Argentina,Bhutan,India,Nepal,Bangladesh
US,Vegetable,2010,Harvested,2.44,T,F,F,F,F,F
US,Vegetable,2010,Yield,15.8,T,F,F,F,F,F
US,Vegetable,2010,Production,6.48,T,F,F,F,F,F
US,Vegetable,2010,Derived Yield,(2.44+15.2)/(6.48+2.66),T,T,F,F,F,F
US,Vegetable,2010,Derived Yield,(2.44+7)/(6.48+5),T,F,T,F,F,F
US,Vegetable,2010,Derived Yield,(2.44+15.2+7)/(6.48+2.66+5),T,T,T,F,F,F
US,Vegetable,2011,Harvested,6,T,F,F,F,F,F
US,Vegetable,2011,Yield,18,T,F,F,F,F,F
US,Vegetable,2011,Production,3,T,F,F,F,F,F
US,Vegetable,2011,Derived Yield,(6+10)/(3+9),T,T,F,F,F,F
US,Vegetable,2011,Derived Yield,(6+2)/(3+3),T,F,T,F,F,F
US,Vegetable,2011,Derived Yield,(6+10+2)/(3+9+3),T,T,T,F,F,F
Argentina,Vegetable,2010,Harvested,15.2,F,T,F,F,F,F
Argentina,Vegetable,2010,Yield,40.5,F,T,F,F,F,F
Argentina,Vegetable,2010,Production,2.66,F,T,F,F,F,F
Argentina,Vegetable,2010,Derived Yield,(2.44+15.2)/(6.48+2.66),T,T,F,F,F,F
Argentina,Vegetable,2010,Derived Yield,(15.2+7)/(2.66+5),F,T,T,F,F,F
Argentina,Vegetable,2010,Derived Yield,(2.44+15.2+7)/(6.48+2.66+5),T,T,T,F,F,F
Argentina,Vegetable,2011,Harvested,10,F,T,F,F,F,F
Argentina,Vegetable,2011,Yield,90,F,T,F,F,F,F
Argentina,Vegetable,2011,Production,9,F,T,F,F,F,F
Argentina,Vegetable,2011,Derived Yield,(6+10)/(3+9),T,T,F,F,F,F
Argentina,Vegetable,2011,Derived Yield,(10+2)/(9+3),F,T,T,F,F,F
Argentina,Vegetable,2011,Derived Yield,(6+10+2)/(3+9+3),T,T,T,F,F,F
Bhutan,Vegetable,2010,Harvested,7,F,F,T,F,F,F
Bhutan,Vegetable,2010,Yield,35,F,F,T,F,F,F
Bhutan,Vegetable,2010,Production,5,F,F,T,F,F,F
Bhutan,Vegetable,2010,Derived Yield,(2.44+7)/(6.48+5),T,F,T,F,F,F
Bhutan,Vegetable,2010,Derived Yield,(15.2+7)/(2.66+5),F,T,T,F,F,F
Bhutan,Vegetable,2010,Derived Yield,(2.44+15.2+7)/(6.48+2.66+5),T,T,T,F,F,F
Bhutan,Vegetable,2011,Harvested,2,F,F,T,F,F,F
Bhutan,Vegetable,2011,Yield,6,F,F,T,F,F,F
Bhutan,Vegetable,2011,Production,3,F,F,T,F,F,F
Bhutan,Vegetable,2011,Derived Yield,(2.44+7)/(6.48+5),T,F,T,F,F,F
Bhutan,Vegetable,2011,Derived Yield,(10+2)/(9+3),F,T,T,F,F,F
Bhutan,Vegetable,2011,Derived Yield,(6+10+2)/(3+9+3),T,T,T,F,F,F
The image of the above expected output data for a structured look at it:
Part 1 -
Part 2 -
Formulae for populating Amount Field for Derived Type:
Derived Amount = Sum of Harvested of all countries with T (True) grouped by Year and Commodity columns divided by Sum of Production of all countries with T (True)grouped by Year and Commodity columns.
So, the target is to have a combination of all the countries from source and calculate the sum of respective Harvested and Production values which then has to be divided. The commodity can be more than one in the actual scenario for any given country, but that should not bother as the summation of amount happens on grouped commodity and year.
Note: The users in the frontend can select any combination of countries. The sole purpose of doing it in the backend rather than dynamically doing it in the frontend is because AWS QuickSight (our visualisation tool), even though can populate sum on selected column filters but doesn't yet support calculation on those derived summed fields. Hence, the entire calculation of all combination of countries has to be pre-populated (very naive approach) in order to make it available in report on dynamic users selection of countries.
Also if you've any better approach (than the above naive approach mentioned in note) to solve this problem, you are most welcome to guide me. I've also posted a question on the same problem without writing my expected approach for experts to show me the path on how we can solve this kind of a problem better than this naive approach. If you want to help solve it with some other technique, you're most welcome, here is the link to that question.
Any help shall be greatly acknowledged.

How to show dimension members for which there are no values in fact in SSAS Multi-Dimensional?

I have two tables in my Ticket Management Application, "ExpositionPeriods" and "OrganisedVisits".
ExpositionPeriods - Defines the periods for which tickets can be purchased.
OrganisedVisits - Stores the tickets purchased information.
In the example below, we have 5 periods available, and tickets have been purchased for 2 of the periods.
The customer wants a report which shows "Number of visitors against each available period". That means if, for any period which doesn't have a visitor, the report should show "0" for that period. Something like this.
So far so good. Since the production database is humongous (~500 GB), it is not advisable to report on this database directly. Things turn to be challenging when I create an OLAP cube out of this schema and try to achieve the same report functionality in the cube. It seems the cube actually performs an action similar to SQL INNER JOIN as opposed to a LEFT OUTER JOIN and hence I do not see those Periods for which there are no tickets sold.
Is this how SSAS actually behaves? Am I missing out any particular setting that will indicate the SSAS engine to process the cube in a different manner so as to include the missing periods as well? Please note, end customers don't have access to MDX/DAX scripts, they can only use the cube by drag-drop measure and dimensions like in Excel pivot table.

In your image the browser is carrying out a non empty on rows on the date dimension. If you want to show the dates with no visitors then select the option to show empty cells.

You can define such scope in "calculations" as
SCOPE
([Measures].[Visitors]);
THIS=IIF(ISEMPTY([Measures].[Visitors]),0,[Measures].[Visitors]);
END SCOPE;
So you have zeros instead of nulls and side effect. You or customer can't hide empty cells, cause now it's not empty enough.

Tableau - Adding dimensions together to show overall revenue

I am very new to Tableau (first day user) and have been a long time Excel user. I am trying to fully understand the power of Tableau to eventually move away from Excel.
I have a question concerning dimensions and creating a calculated field.
My table has multiple categories and sub-categories. My goal is to display the total revenue and average order value per chosen sub-category (this seems easy enough).
I want to then take those sub-categories and show a combined sum of revenue and average of the average order value. I am stuck on trying to also combine these sub-categories to show a blended view.
Furthermore, the 2 sub-categories are weighted very differently. The average order value of 1 has a much heavier weight than the other and will definitely affect the AOV when combined. How do you also assign a weight to this combined total?
Any help will be much appreciated. I know this may be a rather simple solution but I am new to the program and am having difficulty finding this answer.
Tableau screen:
or
img1 http://postimg.org/image/dq5wqgnyl/
Best,
CR

Put sub categories in the rows column.
Put sum revenue in the text pill in the marks section
In the analysis tab on the top select column grand totals.
I'm unable to see your images,i hope this answers a apart of your question.

SSAS - Need to have a calculated member that uses as a denominator one particular dimension value

I have a cube that I built in SSAS for general ledger data. The cube uses 2 fact tables. One for accounts that are "normal" dollar based accounts and the other is for unit / statistical accounts - accounts that count ANYTHING, except for money usually.
I need for one calculated member in SSAS to be ANY of the "normal" dollar based accounts divided by ONLY one particular dimension of the statistical accounts.
If clear as mud - let me give the specific example. There is an statistical account called Gallons (measure is units) and there are many accounts such as sales, depreciation, tax expense, etc that are the "normal" G/L accounts (measure in dollars). I need to have the cube be able to report on ANY of the "normal" G/L accounts DIVIDED by Gallons (so that any of the normal revenue / expense accounts can have a measure that shows BY GALLON.)
I have no clue how to write the MDX to do this (the function to use and / or the syntax) and I have tried many times and researched quite a bit (I am a SQL person - FAR from a MDX person I guess!). I'm thinking I need to use FILTER but I'm not even sure that is the right direction.....

Little unsure with your design ,If you are having trouble with MDX you can create a calculated member in DSV using T-sql

Calculated Member for Cumulative Sum

First some background: I have the typical Date dimension (similar to the one in the Adventure Works cube) and an Account dimension. In my fact table I have daily transaction amounts for the accounts.
I need to calculate cumulative transaction amounts for different accounts for different periods of time. The catch is that whatever is the first period shown on the resulting report should get its transaction amount as-is from the fact table and all the following periods in the report should have cumulative amounts.
For example, I might have a single account on rows and on columns I could have [Date].[Calendar].[Calendar Year].[&2005]:[Date].[Calendar].[Calendar Year].[&2010]. The transaction amount for 2005 should have the sum of transaction amounts that took place in 2005 for that specific account. For the following year, 2006, the transaction amount should be TransactionAmountsIn2005 + TransactionAmountsIn2006. Same goes for the remaining of the years.
My problem is that I don't really know how to specify this kind of calculated member in the cube because the end-user who is responsible for writing the actual MDX queries that produce the reports could use any range of periods on any hierarchy level of the Date dimension.
Hope this made some sense.

Teeri,
I would avoid letting the end-user actually write MDX queries and just force them to use ranges you defined. To clarify, just give them a start and end date, or a range if you will, to select and then go from there. I've worked with accounting and finance developing cubes (General Ledger, etc) for years and this is usually what they were ultimately looking for.
Good luck!