I want to summarize figures for the previous year based on multiple possible selections in Year, Month and Day to provide a previous year comparison on my dashboard: see screenshot.
I have found plenty of working examples for previous year summaries applied to a fixed dimension but none to assist with providing a summary for a range of possible selections.
I have tried numerous set analysis expressions so far, and I have tried adding a variable which calculates 1 year prior and including it in expressions, but the difficulty has been where to include the '1' or select from all possible records in the expression.
Most recent attempt as below calculates but returns 0.
sum( {$<Discharge= {$(#vPrevYr)}>}daycase)
Can anyone assist?
Found the solution:
Changed the variable to
vYearMinus1= Discharge_Year-1
Used in expression
sum({$}daycase)
All hunky dory, selections all (multiple or other) produce previous years figures: Yay!
Table from which figure will be extracted includes the year dimension: see attached screenshots Table including dimensions and finished result Finished result
Related
EDITED (AGAIN): added tables and two screenshots (one of Google Sheets Chart and another showing mutliple issues in DS) to help demonstrate what I am seeing.
Short Version: I have created a parameter to help me score trending topics based on the date range filter. However, I want to be able to show a range of dates' worth of data, not just a specific date's worth of data. In theory, I could make the parameter a checklist with a huge range, but that doesn't seem efficient or sustainable down the road.
Disclaimer: I am about a week into SQL and Data Studio.
Long Version: We are tracking trends over time from a specific customer data set. I'd like to make it so that when a user adjusts the time range, various topics’ " score " depends on the end date. For instance, every time the topic "Recession" is brought up, it is given a score. That score is weighted based on when it was said. I was using 365 as the highest possible score so that anything over a year is null. So if "Recession" is referenced twice, once a week ago and once today, the avg score for recession is 361.5, but if a reference is made to the topic "Talent Management" twice today, then it would have a score of 365, and so forth across a growing list of 50+ topics pertaining to 50+ specific communities we are tracking the topics across.
Here is an example:
topics
groups
entry_date
recession
A
2022-11-24
talent mgt
A
2022-11-24
recession
B
2022-11-22
economy
A
2022-11-22
recession
C
2022-11-15
talent mgt
B
2022-11-8
This score would then affect the bubble size on a chart where the Y-axis is the count of unique groups referencing the topics, and an x-axis based on the range of average scores.
The goal is to be able to see which topics are the most common across groups, which ones are emerging trends, and which ones are dated trends by having a range slider. That way users (colleagues in other departments) can play with the date range "see" the bubbles moving in location and size.
example of static chart in google sheets
I could then also use the same data and fields to measure the percentage of topics being discussed across groups based on the weighted averages against a time range.
In Goolge Sheets I can do this with an xLookUp to a tab that has a column of 0-365 and then next to it a column of 365-0 (on a tab called 'scales') and then a cell on a sheet that you can put any date as the point in time, and it affects all the scores, tables, charts, etc. (I used. =xlookup((point_in_time - entry_date), 'scales'!A:A, 'scales'!B:B, "0")
In the data studios custom SQL I used:
SELECT
*
FROM
`qRaw_data'
where
DATE(_entry_dates_) between
parse_date('%Y%m%d', #DS_START_DATE) and
parse_date('%Y%m%d', #DS_END_DATE)
AND
#pit_date_diff = date_diff(
parse_date('%Y%m%d', #ds_end_date),
_entry_dates_,
day
)
Then I created a field that is time_score of:
avg((Pit_Date_Diff-365)*(-1))
I have been googling and youtubing like crazy and think I either have to come up with a way to override the #pit_date_diff default value OR I need to use a CASE WHEN in the custom query where each time the date_diff is 1 then 365, and so on, but when I try that I get all sorts of errors.
I would like below to include all topics averaged based on all entry dates, not just those that correlate with the inputted parameter field.
currently, I can only show specific entry dates due to the parameter
I appreciate any and all help. I am a week into using data studio and am going cross-eyed Googling and YouTubing things. There is likely a better logical path to accomplish all this. Hoping for a holiday miracle.
Thanks in advance.
It turns out this was much easier than I realized... I added an AS syntax to create a column and then created a field that created the same metrics that I had in the Google Sheets:
SELECT
*,
(date_diff(parse_date('%Y%m%d', #ds_end_date), _entry_dates_,day)) AS q_time_diff
FROM
`qRaw_data`
Then the score field is: (avg(q_time_diff)-365)*(-1)
In case that helps any others in the future... ¯\(ツ)/¯
Happy Holidays!
I am a newbie at Tableau (thought I have spent years working in R and Python), seems to be different in the way it handles things or I'm just not thinking the right way.
I have a data sources with training data (employees training and the status). The point is to build a dashboard that shows the % of training that is overdue. I have all of the logic for it, but I am stuck on something.
I have a calculated field to show me the total training due, then when I put that in a table, with a filter by year and a breakdown by month, I get the totals by month - good deal.
Now, I need to perform an year calculation (not the months, but the year based on a few different things), so my first step is I need to get the "Total Training Due" for December 2018. I have a dimension called "Due Month" which is a numeric (1,2,3,4, etc.) representing the month. So, based on what I have observed, I just need to do a little IF statement like so (keep in mind this is only for 2018 data right now):
IF [Due Month] = MAX[Due Month] THEN COUNT[Employee ID] END
I know this isn't the exact context, but it's sort of what I am looking for. So, for 2018, it would mean that, for all rows that are of month 12, I want to count those up (each row is a unique training requirement) and I want the total for the latest month in the data set. My overall goal is to create the calculation I need in a new sheet with a single calculated field (See the image below of the Excel spreadsheet and the J10 calculation). Then I can use a dashboard to combine everything. I thought about a total row at the bottom, but there isn't enough ways to change the totals to customize it to what I need. I figured I dashboard was the way to go and replicate each part it its own sheet.
I have seen so many suggestion for things like this, but not exactly this. I have tried many, but nothing that works. Here is the spreadsheet I am trying to replicate:
As you can see that calculation in J10 is kind of weird, no biggie for Excel, but I am struggling to replicate this in Tableau. Here is what I have in my Tableau so far, I'm 90% of the way there, I just need that last calculation. I have replicated the main table, and figure I'll do this J10 calc on a new sheet and just put them together on a Dahsboard. The only thing is, I want this to work when new data comes in, so I don't want to hard code any month numbers in there, I want it to be dynamic. Here is what I have on the tableau so far:
Thanks in advance!!
To get the value in Tableau that you have in F11 it's:
{FIXED [Due Year] : sum([Incomplete Overdue])}
You should be able to create that as another calculated field and then reference it, or include it directly in the Total Past Due Rate calculation.
This is an LOD calculation, the [Due Year] means that you only want the result dimensioned by the [Due Year] dimension, so you will get a different result for each year in the data source.
Thanks for this - after posting this, I was able to come up with this:
(TOTAL([Incomplete Overdue]) + SUM(IF ([Past Due]<0 AND INT([Due Month]) = {MAX(INT([Due Month]))}) THEN 1 ELSE 0 END)) / COUNT(IF INT([Due Month]) = {MAX(INT([Due Month]))} THEN [Employee ID] END)
Which works for the basic result I was looking for.
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.
In my SSAS cube, I've several measures defined in MDX which work fine except in one type of aggregation across time periods. Some don't aggregate (and aren't meant to) but one does aggregate but gives the wrong answers. I can see why, but not what to do to prevent it.
The total highlighted in the Excel screenshot below (damn, not allowed to include an image, reverting to old-fashion table) is the simplest case of what goes wrong. In that example, 23,621 is not the grand total of 5,713 and 6,837.
Active Commitments Acquisitions Net Lost Commitments Growth in Commitments
2009 88,526 13,185 5,713 7,472
2010 92,125 10,436 6,837 3,599
Total 23,621 23,621
Active Commitments works fine. It is calculated for a point in time and should not be aggregated across time periods.
Acquisitions works fine.
[Measures].[Growth in Commitments] = ([Measures].[Active Commitments],[Date Dimension].[Fiscal Year Hierarchy].currentMember) - ([Measures].[Active Commitments],[Date Dimension].[Fiscal Year Hierarchy].prevMember)
[Measures].[Net Lost Commitments] = ([Measures].[Acquisitions] - [Measures].[Growth in Commitments])
What's happening in the screenshot is that the total of Net Lost Commitments is calculated from the total of Acquisitions (23,621) minus the total of Growth in Commitments (which is null).
Aggregation of Net Lost Commitments makes sense and works for non-time dimensions. But I want it to show null when multiple time periods are selected rather than an erroneous value. Note that this is not the same as simply disabling all aggregation on the time dimension. The aggregation of Net Lost Commitment works fine up the time hierarchy -- the screenshot shows correct values for 2009 and 2010, and if you expand to quarters or months you still get correct values. It is only when multiple time periods are selected that the aggregation fails.
So my question is how to change the definition of Net Lost Commitments so that it does not aggregate when multiple time periods are selected, but continues to aggregate across all other dimensions? For instance, is there a way of writing in MDX:
CREATE MEMBER CURRENTCUBE.[Measures].[Net Lost Commitments]
AS (iif([Date Dimension].[Fiscal Year Hierarchy].**MultipleMembersSelected**
, null
, [Measures].[Acquisitions] - [Measures].[Growth in Commitments]))
ADVthanksANCE,
Matt.
A suggestion from another source has solved this for me. I can use --
iif(iserror([Date Dimension].[Fiscal Year Hierarchy].CurrentMember),
, null
, [Measures].[Acquisitions] - [Measures].[Growth in Commitments]))
CurrentMember will return an error when multiple members have been selected.
I didn't understand much of the first part of the question, sorry...but at the end I think you ask how to detect if multiple members from a particular dimension are in use in the MDX.
You can examine either of the two axes as a string, and use that to form a true/false test. Remember you can use VBA functions in Microsoft implementations of MDX.
I suggest InStr(1, SetToStr(StrToSet("Axis(1)")), "whatever") = 0 as a way to craft the first argument of your IIF.
This gets the set of members on axis number one, converts it to a string, and looks to see if a certain string is present (it returns the position of that string within the other). Zero means not found (so it returns true). You may need to use axis zero instead, or maybe check both.
To see if multiple members from the same dimension were used, the test string above would have to be more complicated. You want to know if whatever occurs once or twice. You could test if the first occurance of the string was at the same position as the last occurance (by searching backwards); though that could also mean the string wasn't found at all:
IIF(
InStr(1, bigstring, littlestring) = InStrRev(bigstring, littlestring),
'used once',
'used twice or not at all'
)
I came across this post while researching a solution for my own issue with grand totals of calculated measures over time when filters are involved. I think you could have fixed the calculations instead of suppressing them by using dynamic sets. This worked for me.
I am working on SQL Analysis service to provide ad hoc reporting in my application. I have created a time dimension to use in my cube. It has some predefined attributes. e.g. Month of year. It is having values like Month 1, Month 2, etc. while I want January for Month 1, February for Month 2, etc...
Can any one please suggest me some work around it??
As I am newbie to SSAS, Sorry if I am missing something very silly....
When you work with attributes in SSAS, there are two properties that affect the members of that attribute. The first property - which is set by default when you create the attribute - is KeyColumn. The column that you use here determines how many members are in the attribute because processing generates a SELECT DISTINCT statement based on this column. It's a good idea if you use an integer value here for better performance.
It sounds like perhaps you have a month number for your attribute here, which is good. Except that you want to display a month name. In that case, you set the NameColumn property with the column in your data source view that contains the month name. This produces the label that you see when you browse the dimension.
That said, it's usually not a good idea to have just a month number or month name because you probably want to create a hierarchy to roll up months by year and you won't be able to do that with just a month name. I wrote a blog post describing how to set up a date dimension that might help you: http://blog.datainspirations.com/2011/05/11/sqlu-ssas-week-dimension-design-101-2/