I am creating a report in SSRS that shows the duration of phone calls.
In my T-SQL script I am using:
CONVERT(VARCHAR,DATEADD(second,Call,0),108)AS[Call Duration]
which works nicely and shows the time as 00:03:20, for example.
However when I create a table in SSRS and try to sum all the different time values it just says #error in the report. I need the report to be able to add these time values up so I can give a total per switchboard operator. So for example if officer x took three calls and they all lasted 3 minutes then I'd need the total to say 00:09:00
Do you know of a way where I can display the total time spend rather than having to list each value separately? I can sum up the number of seconds for each call - so for example get a total of 540 seconds - but need to show this as hh:mm:ss
Thanks
The report is throwing an error because you are trying to sum up a varchar value. Rather than trying to format your data in your SQL query, simply return the values in their raw form to your SSRS report and let your presentation layer format the data for you.
Rather than using a dateadd, it seems your call length is already held within your Call column? If that is the case, simply return that column to your report, either as detail rows to be summed if the detail is required elsewhere in your report, or pre-aggregated in your SQL as this will perform better.
You can then format your Call Duration as follows:
=format(today().AddSeconds(Fields!Call.Value),"HH:mm:ss")
If you aren't aggregating your call seconds in your SQL query, you will need to do this in your expression:
=format(today().AddSeconds(sum(Fields!Call.Value)),"HH:mm:ss")
Obviously this method assumes you won't have any calls longer than 24 hours. If that is a possibility, you will need to calculate the hours, minutes and seconds to be concatenated together.
Related
I linked Firebase to BigQuery and start using Google Data Studio to create a table to list users by "User Pseudo ID".
My goal is to calculate the difference between two dates, the date of first_open and the date of app_remove to come up with an average retention time.
How can I write the right query in Data Studio?
It can be achieved using the three step process below:
1) HH:MM:SS
The Calculated Field below uses the DATETIME_DIFF function to find the difference between app_remove and first_open, and displays the difference in SECOND (for future reference, set the third input DATETIME_DIFF as required, for example, to view the difference in days, set the input to DAY):
DATETIME_DIFF(app_remove, first_open, SECOND)
2) Type (HH:MM:SS)
Number > Duration (Sec.)
3) Aggregation (HH:MM:SS)
AVG
Google Data Studio Report and a GIF to elaborate:
DATE_DIFF may be what you are looking for.
That is if first_open and app_remove are date fields or date expressions
This should be simple so I think I am missing it. I have a simple line chart that shows Users per day over 28 days (X axis is date, Y axis is number of users). I am using hard-coded 28 days here just to get it to work.
I want to add a scorecard for average daily users over the 28 day time frame. I tried to use a calculated field AVG(Users) but this shows an error for re-aggregating an aggregated value. Then I tried Users/28, but the result oddly is the value of Users for today. The division seems to be completely ignored.
What is the best way to show average number of daily users over a time frame? Average daily users over 10 days, 20 day, etc.
Try to create a new metric that counts the dates eg
Count of Date = COUNT(Date) or
Count of Date = COUNT_DISTINCT(Date) in case you have duplicated dates
Then create another metric for average users
Users AVG = (Users / Count of Date)
The average depends on the timeframe you have selected. If you are selecting the last 28 days the average is for those 28 days (dates), if you filter 20 days the average is for those 20 days etc.
Hope that helps.
I have been able to do this in an extremely crude and ugly manner using Google Sheets as a means to do the calculation and serve as a data source for Data studio.
This may be useful for other people trying to do the same thing. This assumes you know how to work with GA data in Sheets and are starting with a Report Configuration. There must be a better way.
Example for Average Number of Daily Users over the last 7 days:
Edit the Report Configuration fields:
Report Name: create one report per day, in this case 7 reports. Name them (for example) Users-1 through Users-7. These are your Row 2 values. You'll have 7 columns, with the first report name in column B.
Start Date and End Date: use TODAY()-X where X is the number of days previous to define the start and end dates for each report. Each report will contain the user count for one day. Report Users-1 will use TODAY()-1 for start and end, etc.
Metrics: enter the metrics e.g. ga:users and ga:new users
Create the reports
Use 'Run reports' to have the result sheets created and populated.
Create a sheet for an interim data set you will use as the basis for the average calculation. The first column is date, the remaining columns are for the metrics, in this case Users and New Users.
Populate the interim data set with the dates and values. You will reference the Report Configuration to get the dates, and you will pull the metrics from each of the individual reports. At this stage you have a sheet with date in first columns and values in subsequent columns with a row for each day's values. Be sure to use a header.
Finally, create a sheet that averages the values in the interim data set. This sheet will have a column for each metric, with one value per column. The one value is calculated from the series in the interim data set, for example =AVG(interim_sheet_reference:range) or any other calculation you'd like to do.
At last, you can use Data Studio to connect to this data source and use the values. For counts of users such as this example, you would use Sum as the aggregation field type when you are creating the data source.
It's super ugly but it works.
Background Information: We have an incident time tracker that tracks how long each user spends with a representative before the issue can be closed. We want to determine the average volume of incidents that are being handled for each hour. To say this in another way: We want to get an hourly baseline for each day of the week that will show us the average total call length within the specific time period. Eg: We want to average the total length of every call on Monday from 9AM-10AM for all the weeks in the database, and the same for other hourly intervals.
The simplest way to think of this is that I want AVG(SUM) for the specific time periods, but Tableau does not allow me to do this.
Tableau Output:
This is the desired, target visualization that I am looking for from Tableau.
SQL Query:
I have written a SQL query that returns the answer:
We are looking at two columns: start_time (time stamp) and interval_seconds(float)
In the inner query I use the hour_start function which truncates the date/time value to the hour start, so I can group by the hour and day of the week in the outer query.
SQL Results:
Question:
Is there a way to solve this problem ENTIRELY in Tableau that would get me the result that I am looking for without having to write any SQL code?
Files Stored on Drive
CSV File:
https://drive.google.com/open?id=0B4nMLxIVTDc7NEtqWlpHdVozRXc
Tableau Worksheet:
https://drive.google.com/open?id=0B4nMLxIVTDc7M3A4Q0JxbGdlTE0
You can use Level of Detail expressions to compute the SUM(interval_seconds) at the hour level and then use AVG to calculate the number you are looking for.
I created a couple of calculations:
hour which is defined as: DATETRUNC('hour',[start_time])
this should be equivalent to your hour_start(start_time).
and interval_hours which is defined as {FIXED [hour] : SUM([interval_seconds])/3600 }
This calculates the aggregate for each start_time truncated to the hour.
After this, you simply calculate AVG(interval_hours) and use it in your view.
I put a workbook in dropbox: https://www.dropbox.com/s/3hfvz8w529g9f46/Interval%20Time%20Baseline.twbx?dl=0
Although the chart looks similar to yours, the numbers I came up with are somewhat different from the "SQL Results" you show. Was the data you provided slightly different?
I have a PivotTable (actually it is five PivotTables, each on its own separate sheet) that is created from a query of an outside database. Each of the PivotTables represents a day (i.e. Today, Tomorrow, Today+2, Today+3, and Today+4). For the report filter for the first two, we use a date range filter of today and tomorrow which automatically filters the data and allows it to roll over. We created custom date ranges for the other three days, but upon every external data refresh we have to go into each sheet and reselect the report filter from all to the specified time frame. This data rolls over every day so we can see the lineup for the next 96 hours out.
Is there a way to either keep the PivotTable report filter criteria (VBA and macros are both acceptable, although we are also fairly new to both)?
Or is there some super secret way to extend the report filter from just today and tomorrow to a time range (48 hours, 96 hours) instead of next month?
I need the days to be separated, so next week will not work because all the days will populate on one page.
Without seeing a real example it's hard to tell, but how about changing the query to a relative date index, i.e. something like
SELECT DATEDIFF('day', GETDATE(), report_dt) AS days_from_today FROM reporting_table
And then set your report filters on this relative date index (days_from_today = 1 for tomorrow, etc)? You can always create another Excel column in the report =TODAY() + days_from_today to get your absolute date back. (Assuming you are just dealing with one time zone for reporting purposes.)
I.e., instead of rolling filters, keep the filters on constant indices, and let the indices cover a rolling date range. I'm not sure Excel is smart enough to do the rolling filters thing.
I have a WPF app, where one of the fields has a numeric input box for length of a phone call, called ActivityDuration.
Previously this has been saved as an Integer value that respresents minutes. However, the client now wishes to record meetings using the same table, but meetings can last for 4-5 hours so entering 240 minutes doesn't seem very user friendly.
I'm currently considering my options, whether to change ActivityDuration to a time value in SQL 2008 and try to use a time mask input box, or keep it as an integer and present the client with 2 numeric input boxes, one for hours and one for minutes and then do the calculation to save it in SQL Server 2008 as integer minutes.
I'm open to comments and suggestions. One further consideration is that I will need to be able to calculate total time based upon the ActivityDuration so the field DataType should allow it to be summed easy.
The new time datatype only supports 24 hours, so if you need more you'll have to use datetime.
So if sum 7 x 4 hour meetings, you'll get "4 hours" back
How the DB stores it is also different to how you present and capture the data.
Why not hh:nn type display and convert in the client and store as datetime?
Track the start and end time, no need to mask out the date, since the duration will just be a calculation off of the two dates. You can even do this in "sessions" such that one meeting can have multiple sessions (i.e. one meeting that spans across lunch, that shouldn't be counted toward the duration...).
The data type, then is either datetime or smalldatetime.
Then to get the "total duration" it's just a query using
Select sum(datediff(mm, startdate, enddate)) from table where meetingID = 1