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Session connection to Google Sheet exists for 60 minutes. If someone wanted to keep this for more time then "User Login" option requires re-entering credentials every 60 minutes.
However, we can use the Developer Login0 to bypass this limitation. This method requires sign-in using Google API credentials. This option requires obtaining a Client ID, Client Secret, and Refresh Token and does not require re-entering credentials to run a workflow.
My question - can you address this issue in next release of Alteryx?
Python pandas dataframes and data types (numpy arrays, lists, dictionaries, etc.) are much more robust in general than their counterparts in R, and they play together much easier as well. Moreover, there are only a handful of packages that do everything a data scientist would need, including graphing, such as SciKit Learn, Pandas, Numpy, and Seaborn. After utliizing R, Python, and Alteryx, I'm still a big proponent of integrating with the Python language much like Alteryx has integrated with R. At the very least, I propose to create the ability to create custom code such as a Python tool.
Would it be possible to use the ISO week date system, which everybody uses?
In numerous workflows, I used to define the week number of a date with the formula DateTimeFormat(d, "%W") and it was perfectly working till the 1st January, 2019.
But from this date, the week numbers defined by Alteryx are not the same than the ones in the calendar we all use!
Alteryx says that from the 1st to the 6th January, 2019, the week number is "00" instead of "01"!!! And so on until the week 52 which, for Alteryx, goes from the 30th to 31st or December, 2019: the week 52 has only 2 days!!
As the year 2018 begins with a Monday, there is no problem but for 2019 it is completely weird! And it will repeat in 2020...
The rule from the ISO week date system is pretty simple: "The ISO 8601 definition for week 01 is the week with the Gregorian year's first Thursday in it."
Am I the only one that finds it frustrating that when you are summarising values by dates that all the natural sorting is lost. A good example is using the DateTimeFormat function to strip out the days so that you can get monthly totals but this is then saved as a string so time-related ordering is then lost. Is it possible to add the ability to summarise by time periods (weeks, months, quarters, etc....) and for the natural progression of time / days to be maintained as I am constantly having to reinvent the order.
In addition, it would be useful if we could extend this to provide time-based running totals so for example one tool could be configured to point at transaction data (date & value) and would automatically summise the Jan value and then monthly year to date value by period (selected as weekly, monthly, etc...) up to the max date value in the dataset.
I have a large dataset (~200k) of routers with the utilisation figures per month over 36 months. What I have been doing till now is using the TS Model Factory to config and TS Forecast Factory to generate the forecast for the next 6 months grouping by router. Great! Except the values returned per device are exactly the same for the next 6 months. Obviously by not using the ETS / ARIMA macros I lose the ability to configure in more detail.
What I would like is be able to set the parameters of the ETS/ARIMA model in advance then run the batch macro for the number of routers and return a 6 month forecast that takes into account all the parameters.
I had an issue with the ARIMA tool using the R function auto.arima() which missed the obvious seasonality in my data set, but when I manually adjusted Model Customization > Customize the parameters used for automatic model creation > The seasonal components > Alter the degree of seasonal differencing and selected 1, the outputs were much better. The problem is that while this fixes my singular ARIMA model, I want to be able to run this through Model Factory too as I have hundreds of data sets on which I'd have to make this adjustment since auto.arima() misses the seasonality on most of them and produces useless results. Apparently I'm not alone in having this issue as I was directed to another comment thread where someone had the same problem and desired fix as me.
TL/DR version -- please make is possible to manually adjust the parameters of the ARIMA Model Factory tool, or at the very least add the option to alter the degree of seasonal differencing.
And for supporting information, here is my thread:
So I was working on a project which uses the "Download" tool. I needed to measure precisely the response time for each record so I set up a "timestamp" value using the DateTimeNow() function before the actual download. After download was complete, i tried to measure the response time by using the DateTimeDiff() function. However, using this method, i was not able to get a precise (up to a millisecond) performance reading since the DateTime format gets rounded to a second.
It would be great to have a way of precisly measure the time taken for each record to go through a tool or a set of tool and having that value be a part of the output file
I'm stealing this idea from Tableau's number formatting, it's a timesaver.
In the DateTime tool if I've initially selected a value besides Custom in the "Select the format..." list then when I click Custom rather than having the Custom textbox be blank I'd like to have it automatically populated with whatever formatting string I just selected. Here's an example screenshot:
I have a model with an items, date sold and quantity. There are several hundred thousand records for about 10,000 unique items. Is there a way for Alteryx to do a batch forecast to take each item number and forecast it out based on its quantity sold and historical sales? I can do it one item number at a time but can't seem to figure out how to do it all in one model. Attached I have a small sample of the data in a spreadsheet that i'm working with.
Since we know Alteryx uses R for a lot of its predictive and data analysis tools. It takes a while to run the workflow whenever there is R based tool is involved. I was told by a solution engineer that its because its opening and closing R in the background.
Sometimes my workflow has a bunch of tools which are running R in the background and it takes forever to run the workflow.
I think there should be a user setting which allows user to choose if the want to start R along with Alteryx and keep it running in the background.
Hi there, I am looking for examples of financial modelling within Alteryx i.e. Discounted cashflow forecasting - Has anyone seen anything like this before? I've been through some Udemy Alteryx online training, but just can not figure out how to even use the NPV formula in Alteryx. Thanks!
As it is so important to be able to calculate and present time related concepts in modern businesses, it is not possible to have a better output choice? I have seen the reporting chart tool, I have looked at the TS Plot tool and even noticed that the Laboratory Charting tool has disappeared. So can you please provide an output tool that provides some focused functionality on this lacking part?
It was great to find the DateTimeTrim function when trying to identify future periods in my data set.
It would be even better if in addition to the "firstofmonth" , "lastofmonth" there could be "firstofyear", "lastofyear" functionality that would find for instance Jan, 1 xxxx plus one second and Jan, 1 xxxx minus one second. (Dec, 31 xxxx 12:58:59) respectively.
I'm not sure if time down to the second would even be needed but down to the day period.
I will be using TS Model Factory tool for running ARIMA quite extensivelty and understand that existing tool does not allow for model customization options. I will really appreciate if we can have customization options which helps to specify order of AR or MA components like it can be done in ARIMA tool.