Tough problem I am working on here.
I have a table of CustomerIDs and CallDates. I want to measure whether there is a 'repeat call' within a certain period of time (up to 30 days).
I plan on creating a parameter called RepeatTime which is a range from 0 - 30 days, so the user can slide a scale to see the number/percentage of total repeats.
In Excel, I have this working. I sort CustomerID in order and then sort CallDate from earliest to latest. I then have formulas like:
=IF(AND(CurrentCustomerID = FutureCustomerID, FutureCallDate - CurrentCallDate <= RepeatTime), 1,0)
CurrentCustomerID = the current row, and the FutureCustomerID = the following row (so it is saying if the customer ID is the same).
FutureCallDate = the following row and the CurrentCallDate = the current row. It is subtracting the future call time from the first call time to measure the time in between.
The goal is to be able to see, dynamically, how many customers called in for a specific reason within maybe 4 hours or 1 day or 5 days, etc. All of the way up until 30 days (this is our actual metric but it is good to see the calls which are repeats within a shorter time frame so we can investigate).
I had a similar problem, see here for detailed version Array calculation in Tableau, maxif routine
In your case, that is basically the same thing as mine, so you could apply that solution, but I find it easier to understand the one I'm about to give, I would do:
1) Create a calculated field called RepeatTime:
DATEDIFF('day',MAX(CallDates),LOOKUP(MAX(CallDates),-1))
This will calculated how many days have passed since the last call to the current. You can add a IFNULL not to get Null values for the first entry.
2) Drag CustomersID, CallDates and RepeatTime to the worksheet (can be on the marks tab, don't need to be on rows or column).
3) Configure the table calculation of RepeatTIme, Compute using Advanced..., partitioning CustomersID, Adressing CallDates
Also Sort by Field CallDates, Maximum, Ascending.
This will guarantee the table calculation works properly
4) Now you have a base that you can use for what you need. You can either export it to csv or mdb and connect to it.
The best approach, actually, is to have this RepeatTime field calculated outside Tableau, on your database, so it's already there when you connect to it. But this is a way to use Tableau to do the calculation for you.
Unfortunately there's no direct way to do this directly with your database.
Related
Require assistance in calculating the Total Active Users from March 16 2020 to Feb 16 2020.
I have tried using calculated fields, but not getting the correct results. Please advise.
Thank you,
Nirmal
To find the number of unique values that appear in a field, say [user_code], you can use the COUNT DISTINCT function, COUNTD() as in COUNTD([user_code])
To restrict the data to a particular time range, one way is put your date field on the Filter shelf and choose the settings that include only the data rows you want — say the range from 2/16 to 3/16 as you stated.
Alternatively, you can push the filtering condition into the calculation with an IF function call, as in COUNTD(IF <data is relevant> THEN [user_code] END) Thus effectively combining the two techniques. That works because if there is no ELSE clause and the IF condition is False then the IF statement evaluates to null. Since COUNTD() silently ignores nulls, like other aggregation functions, the expression acts as if the irrelevant data rows were filtered.
So, for example,
COUNTD(IF [dates] >= #2/16/2020# AND [dates] <= #3/16/2020# THEN [user_code] END)
Will tell you then number of unique user codes during the period between 2/16 and 3/16. The DateDiff() function will probably be useful in more elaborate tests.
Finally, what if you want more flexibility? You could easily use Parameters or Filter controls to let the user choose the date range interactively.
If you want this calculation repeated for each possible day, showing the unique users in the preceding 30 day period, as some sort of rolling calculation, then you’ll need to learn about some more advanced features. Either multiple calculations as above for different time ranges, using Table Calculations, or some data prep and/or data padding with Tableau Prep Builder, Python or some other technique — mostly because in that scenario each data row contributes to multiple rolling counts, rather than one count when partitioning the data by some dimension.
I have been struggling to find the new incoming volume per day.
I have categories as : - total ticket, Resolved, closed and Daily left.
So the calc is everyday resolved and closed are moved from the queue and
'daily left = Total Ticket- (Pending + Closed)'
Now there is some carry forward everyday hence the total ticket for the next day includes some volume i.e. Daily left of previous day.
I am not able to figure out how to show that number, I have tried using previous value but it is not helping. Please suggest. Attaching a print screen of the data.
For 3rd the # of records are 33 however there is 1 carry forward from previous
day hence the Fresh Vol should be 32. I have used the formula to calc but it is
not giving correct result
sum([Number of Records]) - (PREVIOUS_VALUE([Daily Left Volume]))
This is taking the left over of current day and not previous day.
I am also using look Up function but that also does not show the current output.
The output from tableau after using the lookup function is below attached as well
I am new to this community and dont have enought reputation to comment :P. So writing few possible solutions here:
1) Make sure the data is sorted by date and is unique on date level. If it is not then Previous or lookup might not work
2) Another solution will be take running_sum of every field and then apply the operations. This should give right answer
3) If this does not will it possible to change the way you import the data?
a) Simply create another filed as Date_past = Date-1 in your raw data.
b) Duplicate your data.
c) join the two data sets on Date = Date_past
d) Now you have all the data of today's date and last day in one field and you can perform operations as you need
I will try to explain the problem on an abstract level first:
I have X amount of data as input, which is always going to have a field DATE. Before, the dates that came as input (after some process) where put in a table as output. Now, I am asked to put both the input dates and any date between the minimun date received and one year from that moment. If there was originally no input for some day between this two dates, all fields must come with 0, or equivalent.
Example. I have two inputs. One with '18/03/2017' and other with '18/03/2018'. I now need to create output data for all the missing dates between '18/03/2017' and '18/04/2017'. So, output '19/03/2017' with every field to 0, and the same for the 20th and 21st and so on.
I know to do this programmatically, but on powercenter I do not. I've been told to do the following (which I have done, but I would like to know of a better method):
Get the minimun date, day0. Then, with an aggregator, create 365 fields, each has that "day0"+1, day0+2, and so on, to create an artificial year.
After that we do several transformations like sorting the dates, union between them, to get the data ready for a joiner. The idea of the joiner is to do an Full Outer Join between the original data, and the data that is going to have all fields to 0 and that we got from the previous aggregator.
Then a router picks with one of its groups the data that had actual dates (and fields without nulls) and other group where all fields are null, and then said fields are given a 0 to finally be written to a table.
I am wondering how can this be achieved by, for starters, removing the need to add 365 days to a date. If I were to do this same process for 10 years intead of one, the task gets ridicolous really quick.
I was wondering about an XOR type of operation, or some other function that would cut the number of steps that need to be done for what I (maybe wrongly) feel is a simple task. Currently I now need 5 steps just to know which dates are missing between two dates, a minimun and one year from that point.
I have tried to be as clear as posible but if I failed at any point please let me know!
Im not sure what the aggregator is supposed to do?
The same with the 'full outer' join? A normal join on a constant port is fine :) c
Can you calculate the needed number of 'dublicates' before the 'joiner'? In that case a lookup configured to return 'all rows' and a less-than-or-equal predicate can help make the mapping much more readable.
In any case You will need a helper table (or file) with a sequence of numbers between 1 and the number of potential dublicates (or more)
I use our time-dimension in the warehouse, which have one row per day from 1753-01-01 and 200000 next days, and a primary integer column with values from 1 and up ...
You've identified you know how to do this programmatically and to be fair this problem is more suited to that sort of solution... but that doesn't exclude powercenter by any means, just feed the 2 dates into a java transformation, apply some code to produce all dates between them and for a record to be output for each. Java transformation is ideal for record generation
You've identified you know how to do this programmatically and to be fair this problem is more suited to that sort of solution... but that doesn't exclude powercenter by any means, just feed the 2 dates into a java transformation, apply some code to produce all dates between them and for a record to be output for each. Java transformation is ideal for record generation
Ok... so you could override your source qualifier to achieve this in the selection query itself (am giving Oracle based example as its what I'm used to and I'm assuming your data in is from a table). I looked up the connect syntax here
SQL to generate a list of numbers from 1 to 100
SELECT (MIN(tablea.DATEFIELD) + levquery.n - 1) AS Port1 FROM tablea, (SELECT LEVEL n FROM DUAL CONNECT BY LEVEL <= 365) as levquery
(Check if the query works for you - haven't access to pc to test it at the minute)
I'm currently struggling with a calculation I'm trying to create in Tableau so any help you can provide would be great.
Basically I have a calculated field within Tableau called [ExampleCount] which is a count distinct based on a simple Yes/No condition.
I have this information displayed on two separate sheets in a dashboard, one filtered for the current activity month and one for the previous.
What I now need to do is have another sheet with the same calculation of [ExampleCount] but showing the difference between the current/previous months.
So: [ExampleCount (This Activity Month)] - [ExampleCount (Previous Activity Month)]
The Activity month is an integer value, currently ranging from 1 - 9.
I feel like this should be a simple calculation but I've tried several different methods and have been unable to come up with anything conclusive.
It would also be good if this could change periodically.
Kind Regards,
Plain_Lazy
I want to set the default range on a date filter to show me the last 10 days - so basically looking at the lastDate (max date) in the data and default filtering only on the last 10 days (maxDate - 10)
How it looks now:
I still would want to the see the entire range bar on the dashboard and give the user the ability to modify the selected range if he wants to. The maxDate changes after every data refresh so it has to be some sort of a condition that is applied to the filter.
How I want it to look (by default after every refresh of data - new dates coming in):
Any suggestions on how this can be done? I know I can use the relative date and show the data for last 10 days but that would modify the filter and create a drop down which I don't want.
Any suggestions are welcome!
One simple approach that does most of what you want is the following:
Create an integer valued parameter with a range from 1 to some max
you choose, say 100. Call it say num_days.
Show the parameter control on your dashboard as a slider, and give
it a nice title like "Number of days to display"
Create a boolean calculated field called Within_Day_Range defined as:
datediff('minute', [My_Date_Field], now()) < [num_days] * 24 * 60
Put Within_Day_Range on the filter shelf and select the value true.
This lets the user easily select how many days in the past to include, and works to the granularity of minutes (i.e. the last two days really means the last 48 hours, not starting at midnight yesterday). Adjust the calculated field if you want different behavior.
The main drawback of this approach as described so far is that it doesn't display the earliest date possible in the database because that is filtered out. Quick filters do an initial query to get the bounds, which has a performance cost -- so using the approach described here can avoid that query and thus load faster.
If you really need that information on your dashboard, you could create a different worksheet to get just the min([My_Date_Field]) and display that near your parameter control.