I have a fact table housing different granularity (date grain)
Monthly
Daily
The month data can be accessed by filtering by end of month date or using YYYYMM date format. In OBIEE RPD repo, the fact is set to LAST Aggregation.
I want to perform Year to Date analysis. And I want to sum only month end dates.
Using function TODATE(Measure), it tends to sum up all the data through out the month e.grain
Date Amount YTD TODate(Amount)
31/01/2106 100 100
28/02/2016 200 300
14/03/2016 50 350*
31/03/2016 100 450
I want YTD to ignore 50 and return 400, so also any other dates that falls within any month. And if if I Select 14/03/2016 I want 350 to return.
Thanks.
Alter the table to add a flag, something that flags Y if the record is at the specified monthly grain, and N if the record is not at the specified monthly grain.
In the logical layer, create two distinct LTSs with the first filtering on the flag for Y. This will be where you will calculate and source all your to date measures. The second LTS can either be filtered to N, or can be left to all the data depending on what you want to do with it.
The performance increases should come from the fact that any month measures you build off that monthly LTS will only hit records flagged as month, and will bypass all that other data that is not relevant. So if a user runs a report only asking for monthly measures, the query will automatically filter to that specific data.
What will happen is if a user selects your to date measure and a specific date measure on the same report, OBIEE should fire off two separate queries to get the data and stitch together based on common dimensions.
Could someone create this in the front end? Probably. You would have to do some sort of PERIODROLLING function, and tell it to aggregate at the month level, but I am afraid it may still roll those days up into a larger than desired number. A TODATE function will not work here.
Related
I'm trying to create some measures using DAX on an underlying data model which I would then use for creating some visuals (line chart, bar chart etc.). Each table in the data model has a data field (date&time) that contains repeated dates and times (more occurencies with the same date&time). To use the metrics in the visuals I need the measures to be grouped for date (only date, not for time).
To achieve the task I've created a calendar table (using CALENDAR in DAX) to set-up a set of dates (only dates) to which refer at for every table in the data model and created relations (dates that points to calendar date) for every table. I set the upper limit of the calendar table to be a year ahead of the max date in the dataset, because some measures need to be evaluated in the future.
In the visual pages, I put a slicer that points to the calendar table dates, but the date interval is too wide. I need the slicer to have a more narrow interval, let's say, only "for the present and the past" but I prefer not to add another calculated table.
In your opinion, is there a way to limit the slicer without changing its reference to the calendar table?
Thanks!
For the calendar you may just use CALENDARAUTO(). It will expand automatically as the data model expands.
For the slicer, just select it, open the filter pane and define a filter with the upper limit you want.
You can use combination of 3 different slicer for your purpose. This is just another option that you can have a look on. There will be 3 slicer for Year, Month & Date. So Date slicer is you final slicer, with 2 other slicer on top of it to generate necessary Dates in the slicer. This way, you are not making any static restriction to generate the Date list but giving the user full control on the Date range. Here below is a sample how the slicers can be look in practical.
User can select any year or multiple year, any month or multiple month. Finally the date slicer will hold Date values accordingly.
I need to be able to filter my data to comparable weeks/months across various years. And I need to be able to update those choices on the fly. Is there a way in tableau to set a non-continuous date filter?
because the base data is saved on the tableau server, I'm unable to join additional tables to it, so my initial idea of making a table of year / start date / end date and joining that to my data with a simple t/f filter isn't panning out.
I've considered making series of parameters, but it seems like it might get a bit overwhelming to make so many
Other things I've considered is writing an extended rule like
IF [year] = 2015 THEN [date]BETWEEN(date A, date B)
or the tableau equivalent to BETWEEN
ELSEIF [year] = 2016 THEN [date]BETWEEN(date C, Date D)
ELSE IF //and so forth
Does anyone else have experience with this? Any strategies you might recommend on the parameters vs. a long formula?
Any ideas are greatly appreciated!
Standard tableau filters on dates allow filtering by both continuous date ranges or filtering by parts of dates.
For example, if you wanted to compare January sales cross multiple years, you can drag your date field to the filters shelf and then right-click the date field in the shelf and choose "Discrete" rather than "Continuous" or choose "Month" in the upper set of options about which date component you want (the upper set selects date components, the lower set selects date ranges with in filters and axes).
So, if you put a date field on the filters shelf and select "month" as a discrete you will get a filter that allows you to filter for every January in the dataset.
Let's say I have a date dimension and from my business requirements I know that the most granular I would need to go is to examine the specific day of the month that an event occurred.
The data I am given provides me with the exact time that an event occurred (YYYY-MM-DD HH:MM:SS). I have two opitons:
Before loading the data into the date dimension, slice the HH:MM:SS from the date.
Create the time attributes in my date dimension and insert the full date time.
The way I see it, I should go with the option 1. This would remove redundant data and save some space. However, if I go with option 2, should the business requirements ever change or if my manager suddenly wants to be more granular I wouldn't need to modify my original design. Which option is more commonly used? Are there more options that I did not consider?
Update - follow up question
I receive new data every month. If I used a pre built date dimension with all the dates would I then need to run my script every month to populate the table with new dates of that month or would I have a continuous process where by every day insert into the table one row, which would be that date?
I would agree with you and avoid option 2. A standard date dimension table is at the individual date level. If you did need to analyse by time of day, you could create an additional time of day dimension at the level of a second in a single day, and link to that from your fact table.
Your date dimension should be created by script automatically, rather than from the dates that events occurred. This allows you to analyse across a range of events from other facts, and on dates where no events occur, using a standard, prebuilt dimension.
I would also include the full date/time stamp as a column in the fact table, along with the 'DateKey' to the dimension table. This would allow you some visibility/analysis of the timestamp, you would not lose the data, and would still allow you to analyse by the date dimension.
Update - follow up question
Your pre-built date dimension (the standard way of doing it) would usually contain some dates in the future. There's no reason not to, for example, include another 5 years of dates in the table. But if you'd like it to gradually grow over time, you could have a script that is run once a day, once a month, or once a year to add new dates. Its totally up to you! There are many example scripts for building date dimensions- just google date dimension script. They exist for the language of your choice, e.g. SQL, C#, Power Query, etc.
I need to build a calculation that takes into account whether or not someone checks on a day in Tableau. Currently using Tableau 10.0.5.
For instance, say I have the following data
Date Amount
1-Oct 100
1-Oct 120
2-Oct 150
3-Oct 200
4-Oct 250
5-Oct 500
I need a way to calculate the total amount for the days that are checked in a filter. So, if a user selected Oct 1 to Oct 3, the amount would be $570. Any ideas on how to make this happen are appreciated.
I know how much we all love to work with dates in Tableau! :-)
If you are not showing dates in your viz then simply sum([Amount]) will give you the sum of amount for selected dates.
In case you want to show individual dates and sum of sales across all dates you will have to use Level of Detail Expression
{ EXCLUDE [Date]:SUM([Amount])}
Here is the URL for Example
Could someone please explain me creating BINS based on Weekdays in Tableau? I tried creating different Calculation Fields but it won't work
You're working too hard.
Tableau already knows how to bin values by dates at many levels of granualarity: such as year, month, day, weekday, hour etc. So you don't need to create a new field to bin dates by the day of the week. (creating bins is not difficult, it's just already available in this case)
Just put a discrete (blue) date or datetime field on a shelf. You'll see the date level of granularity displayed like, say, YEAR(MyDateField) with a leading plus sign.
You can either
click on the plus sign to drill down by adding a second level, say MONTH(MyDateField)
or
right click on the field to select the date level of granularity you want
Alex's Answer is exactly correct, Tableau will perform the operation automatically. What is great about is that you can select various formats (Full day name, number, 1 letter or 3 letter day etc.).
However if you absolutely need to you can used this formula:
datepart('weekday',[Date])
to give you the 1 (Sunday) to 7 (Saturday) value if you need it for something other reason, say another calculation.