This one is kind of weird and my lack of experience has me asking this.
I have an update to do and because of how bad the tables are put together where I'm grabbing this data it makes it a bit difficult.
The scenario:
There could be 1 to x amount of Visits per Patient. I want to grab the last visit. Here is where the problem is - one patient can have two or three IDs. These IDs are linked to ONE ID to help migrate them over to a new database and under one ID.
Now I've tried top 1 in a cross apply and a joining on a maxid. I can get some of it to work but not all. So I used a row number ranking to get how many times a particular person visited. However I have to run a pass on the update for each visit to get the last one as it will overwrite the previous.
Is there a way to use row_number() over (partition by B.Uid order by B.Uid) PID
So I would run a pass where pid = 1 then another pass on where pid = 2 and so on.
I am thinking there must be a way to have it do one pass - either by setting up some while loop or checking to see the highest PID then update.
Related
I have a query from another thread which goes through a list of different events and pulls out the most recent event and puts it into a list. The code I'm using is:
SELECT Cleaning1, Max(Date1) AS most_recent
FROM CleaningLog
GROUP BY Cleaning1;
Cleaning1 is the column that has the different cleanings, and Date1 is the column that has the date the cleaning occurred, and CleaningLog is the name of the table. I currently have a macro in Access which is an OpenQuery, query. I am having it open the above query, and then having it view as a data sheet and it's in edit mode.
What I am stuck on, is getting a subsequent macro/query/vba code to take the datasheet the query produces and going through each item and determining if they're over due to be cleaned. I tried having a Make Table query, but the problem is, there is no user friendly way to refresh that table without having to delete it (I am having unskilled workers use this Access sheet).
I am wondering if there's a way to look at the most recent cleaning's date, what the query produces, and filter the dates out that are over due for a cleaning, specified by a parameter. I have been looking at this webpage to start playing with the notation, but I haven't been able to come up with much that is useful.
https://support.office.com/en-us/article/Examples-of-query-criteria-3197228C-8684-4552-AC03-ABA746FB29D8
Another problem that I am encountering is that each cleaning doesn't have the same time frame in which is needs to be cleaned.
Thank you in advance for any help!!
You should just be able to modify the query above to show entries with a max date lower than they should be. Below shows entries that haven't been cleaned in 30 days, for instance.
SELECT Cleaning1, Max(Date1) AS most_recent
FROM CleaningLog
GROUP BY Cleaning1
HAVING Max(Date1) < Now() - 30;
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 have an incident queue, consisting of a record number-string, the open time - datetime, and a close time-datetime. The records go back a year or so. What I am trying to get is a line graph displaying the queue volume as it was at 8PM each day. So if a ticket was opened before 8PM on that day or anytime on a previous day, but not closed as of 8, it should be contained in the population.
I tried the below, but this won't work because it doesn't really take into account multiple days.
If DATEPART('hour',[CloseTimeActual])>18 AND DATEPART('minute',[CloseTimeActual])>=0 AND DATEPART('hour',[OpenTimeActual])<=18 THEN 1
ELSE 0
END
Has anyone dealt with this problem before? I am using Tableau 8.2, cannot use 9 yet due to company license so please only propose 8.2 solutions. Thanks in advance.
For tracking history of state changes, the easiest approach is to reshape your data so each row represents a change in an incident state. So there would be a row representing the creation of each incident, and a row representing each other state change, say assignment, resolution, cancellation etc. You probably want columns to represent an incident number, date of the state change and type of state change.
Then you can write a calculated field that returns +1, -1 or 0 to to express how the state change effects the number of currently open incidents. Then you use a running total to see the total number open at a given time.
You may need to show missing date values or add padding if state changes are rare. For other analytical questions, structuring your data with one record per incident may be more convenient. To avoid duplication, you might want to use database views or custom SQL with UNION ALL clauses to allow both views of the same underlying database tables.
It's always a good idea to be able to fill in the blank for "Each record in my dataset represents exactly one _________"
Tableau 9 has some reshaping capability in the data connection pane, or you can preprocess the data or create a view in the database to reshape it. Alternatively, you can specify a Union in Tableau with some calculated fields (or similarly custom SQL with a UNION ALL clause). Here is a brief illustration:
select open_date as Date,
"OPEN" as Action,
1 as Queue_Change,
<other columns if desired>
from incidents
UNION ALL
select close_date as Date,
"CLOSE" as Action,
-1 as Queue_Change,
<other columns if desired>
from incidents
where close_date is not null
Now you can use a running sum for SUM(Queue_Change) to see the number of open incidents over time. If you have other columns like priority, department, type etc, you can filter and group as usual in Tableau. This data source can be in addition to your previous one. You don't have ta have a single view of the data for every worksheet in your workbook. Sometimes you want a few different connections to the same data at different levels of detail or for perspectives.
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.
I have a report that I've written and I understand how to create running totals and such, but need help creating a custom evaluation formula.
I have two levels of groups, first group is based upon a certain user, the next group is based upon transactions that user has been involved in. I have details hidden, and am only interested in the totals for a particular activity. This is working great, and totals are working properly but the problem is, each activity has a 'line number', which essentially can be the same as another activity (ie: two activities can have lines 1, 2, 3 contained within), so doing a distinctive total based upon a set of data isn't accurate because I only want it to be distinct based upon each individual recordset, and not globally.
The example is below... if I do a count on each record for this dataset, it comes out to 18 because there are duplicate line numbers on each... but if I do distinct, it only comes to 9 because of duplicate line numbers across multiple actives.
I guess what I need to know is how I can take the totals per detail group, and have them total up in my second footer properly. I assume it's going to take me compiling together a string including the activity number and line number, and then comparing them?
Here is an example of the data contained within the total groupings:
I figured this out on my own... turned out it was pretty simple. I converted my numeric values to text, and included a copy of the transaction id and the line id as my test value, and did distinct on that... Sometimes it just helps not staring the problem down.