I am using a free development account, rails 4.0, ruby v2, heroku toolbelt, redis-server, and postgres 9
I have a rails app that had been loading transactions from Aug. 2013 to Feb. 2014 this past Feb..
In March the app loaded back to Sept., saw that we had hard-coded 7 months, so I switched to load 9 months. The transactions will not load farther back than Sept., both for the cc bank test accounts and a personal bank of america account. It will load a shorter time period(3 months) but calls further back than 7 months only load 7 months.
the main calls I'm making
def services
IntuitIdsAggcat::Client::Services
end
def fetch_transactions
#transactions = services.get_account_transactions(
account.user.intuit_id, account.intuit_id, 9.months.ago
)
end
Is there a limit on how far back you can look at transactions with the free development account?
Thank you for your time
This is what I got from Intuit APP team - it sucks :)
We only capture 180 days prior to the add day and that is dependent on the FI. Some FIs we can only get 90 days at most.
Related
I schedule the transfer to run at around 4 am every day and it usually returns data with product_data_timestamp for the day before. However, today it only returns data with product_data_timestamp for 2 days ago. I've tried to run the transfer again at 11 am and create a new transfer at 2 pm but it still doesn't return product_data_timestamp for yesterday but 2 days ago. I have never seen this happen before. Do you have any idea why and how to solve this? Thanks in advance.
I am trying to do some automated reports on Chrome OS devices we have.
I would like to have the number of devices that get used the last 7 days, and the same for the month.
Google Admin Reports can give me a CSV file with how much devices get used the last seven days, but not automatically, and I can't change the 7 days for a month.
I think it is possible to do this using GAM (Google Application Manager), but I can't manage to get the right results.
Tried "gam print cros query "sync:yyyy-mm-dd..yyyy-mm-dd"" but it doesn't give me the same result as Google Admin Reports.
Do someone have a clue on how to do this ? Even eventually how to automate it ?
For those who want to do the same and export it on a .csv file :
For Chromebook activity on 7 days :
gam report usage customer parameters cros:num_7day_active_devices > C:\GAM\Activity_7days.csv
For Chromebook activity on 30 days :
gam report usage customer parameters cros:num_30day_active_devices > C:\GAM\Activity_30days.csv
I’m a data analyst in the insurance industry and we currently have a program in SAS EG that tracks catastrophe development week by week since the start of the event for all of the catastrophic events that are reported.
(I.E week 1 is catastrophe start date + 7 days, week 2 would be end of week 1 + 7 days and so on) then all transaction amounts (dollars) for the specific catastrophes would be grouped into the respective weeks based on the date each transaction was made.
Problem that we’re faced with is we are moving away from SAS EG to GCP big query and the current process of calculating those weeks is a manually read in list which isn’t very efficient and not easily translated to BigQuery.
Curious if anybody has an idea that would allow me to calculate each week number in periods of 7 days since the start of an event in SQL or has an idea specific for BigQuery? There would be different start dates for each event.
It is complex, I know and I’m willing to give more explanation as needed. Open to any ideas for this as I haven’t been able to find anything.
I'd like to estimate the value of each "conversion" starting from a free trial signup all the way to that user becoming a paid user.
Let's say I have an online coding course website that offers a free 30-day trial. After the trial period, the cost is $100 per month.
I bring in 100,000 users/mo to the signup page of my site via Google Ads paid search
I consistently get ~1,000 free trial signups per month (1% conversion rate). All signups are considered free trial users
Of the 1,000 trial users, 500 log in exactly 2x within the first week (let's call these L2W1 for Logged in 2x within Week 1)
Of the 1,000 trial users, 100 log in at least 3x within the first week (L3W1). These users are mutually exclusive from above
Of the 500 L2W1 users, 50 users (10%) sign up for at least 1 course
Of the 100 L3W1 users, 50 users (or 50%) sign up for at least 1 course
On average, I get 35 paid users monthly
10 of 50 L2W1 users become Paid Users
25 / 50 L3W1 - in other words, 50% of L3W1 Users convert to a Paid User
To recap, assume these are the only events that I am currently tracking:
100,000 Site Visitors ---> 1,000 Trial Signups
500 L2W1 ---> 50 Course Signups (CS) ---> 15 Paid Users = $1,000
100 L3W1 ---> 50 Course Signups (CS) ---> 35 Paid Users = $2,500
Total: 35 Paid Users (PU) ---> $3,500
To keep things simple, let's ignore life-time value (e.g. the average user subscribes for 3.5 months).
QUESTION: Is there a mathematical equation I could use to assign values (or percentages) to each conversion event? As I receive more information, I'd like to provide that to Google as a signal that each conversion type down the funnel is a sign of a more qualified user and therefore more valuable to my business.
I can simply take the 1,000 Trial Signups and divide $3,500 (and ignore all other conversion types) in which case each Trial Signup is worth $3.50. However, only 35/1000 Trial Users convert to a Paid User so there is valuable information I am leaving on the table and not informing Google for automated bidding purposes.
I'm thinking something like this is better:
1 Trial Signup = $1.00
1 L2W1 = $2.00
1 L3W1 = $3.00
1 CS = $4.00
1 PU = $90.00
.. so a Paid User who goes through several of the steps above will equate to about $100. Not sure if this is a good approach or if the math makes sense. Any pointers or tips would be greatly appreciated.
I've been reading on Bayes Theorem and it seems to be a good model to use for this case but I'm not at all familiar with it enough to know if it's applicable to this situation.
how can I see data for last month in Fabric Answers? Or is it just for last 30 days overview
I looked all documents on Fabric Answers website, blog and read almost every question here, but I have seen only data for 1 day, last 7 days or last 30 days.
Fabric/Firebase here - it depends what you're looking for. If you're talking about the active user categories, the dashboard will show you Daily Active Users (1 day), Weekly Active Users (7 days), or Monthly Active Users (30 days). If you just want Answers data that's more than 30 days old in general, you can actually export up to a year's worth of data directly from the Fabric dashboard for many different metrics. Check out this link for more information: https://docs.fabric.io/android/answers/export-data.html. Hope that answers your question.