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!
Related
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.
I am new to OLAP and I have a pretty tricky assignment that I am not sure is possible in MDX:
I work for an insurance company and I have been asked to provide a Retention Rate calculation to compare the number of policies we have kept from one time period to another.
The data in our fact table consists of a month-end snapshots of each our policies and there is a flag to indicate whether they are currently active at that time.
So, in plain English, the steps to find the Retention Rate from December 2014 to December 2015 would be:
Get the set of active policy IDs as of December 2014 (set #1)
Get the set of active policies as of December 2015 that have the SAME policy ID as set #1 (set #2)
Divide set #2 by set #1 to get the Retention Rate
I am just not sure if it is possible to compare specific IDs from two different sets like that in MDX.
Any help would be greatly appreciated!!
This isn't something one would normally use MDX for, since it involves a condition at the detail level (PolicyID), and MDX is all about data in aggregate.
However, if you are willing and able to add a flag to your fact table/view it can be done. To address your exact question, you could simply add a bit (or int) flag into your fact table. For each record, the flag would be true (1) if the PolicyID is active now AND was active a year ago, and false (0) if it was not.
Then you can add a new measure to your cube that counts "retained policies", which is just the sum of the flag you just added, and then you can easily divide one measure by another.
If your needs are more complex than this one instance, there might be ways to add more complex data, but the point is that you have to create a way for your cube to be able to compare aggregations.
I have a problem here, i would like to sum the work time from my employee based on the data (time2 - time 1) daily and here is my query:
Effective Minute Work Time = 24. * 60 * (LASTNONBLANK(time2,0) -FIRSTNONBLANK(time1,0))
It works daily, but if i drill up to weekly / monthly data it show the wrong sum as it shown below :
What i want is summary of minute between daily different times (time2-time1)
Thanks for your help :)
You have several approaches you can take: the hard way or the easier way :). The harder (at least for me :)) is to use DAX to do this. You would:
1) create a date table,
2) Use the DAX calculate function to evaluate your last non-blank and first non-blank values (you might need to use calculate table, but I'm not sure; DAX experts jump in). Then subtract one vs. the other.
This will give you correct values for a given day for a given person. You can enforce the latter condition by putting a 'has one value' guard on the person name so that your measure informs the report author if they're not using it right.
Doing the same for dates is a little trickier. In the example you show you are including the date in the row grouping. But if you change your mind and want instead to have 'total hours worked by person' or 'total hours worked by everyone' you're not done with modelling yet.
Your next step is to use calculate table in combination with calculate to create a measure that returns the total. You'll use calculate table so you evaluate each date and the hours worked on that date by person. Then you'll use calculate to summarize that all down to a single number. If you're not careful with your DAX (or report authoring) you might mix which person you're summarizing for so that your first/last non blank are not at the person level. It gets intense quickly.
Your easier solution, though it might be more limited in its application - depends really on your scenario - is to use the query to transform the data into a summary by day and person using the group by command. This will give you a row per person per day with their start and end times. Then you can quickly calculate the hours worked on that day. Then you can quite easily build visuals on top of the summary data. Of course you give up some of the flexibility of the having a proper data model. However if you have a date table, a person table, and your summary table and then setup your relationships correctly you can achieve answers to the most common questions.
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.
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