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MauricioANew Participant

Update BDIA Response to be Explicit when File Upload Fails due to Known LimitationsNew

Description - In the documentation for the BDIA (Bulk Data Insertion API), there are 5 Limitations on uploads. One is the requirement that the report suite be configured as "Timestamp Optional" or "Timestamp enabled."  Last month, my team began uploading files using the BDIA for the first time. After each upload, the API provided a response that suggested the upload was successful (see an excerpt of the API response below). However, our QA efforts showed that the data was not present in Analytics even after days of uploads. We eventually determined through other means that the root cause was that the report suite had not been set to "Timestamp Optional". The data uploads were failing, yet the API response did not reflect this.Why is this feature important to you - The data we were uploading is critical for some of our business processes, and those processes were delayed while we investigated the root cause of the failed uploads. We also spent more engineer time than necessary while deep diving, since the "Processing complete" API response led us to investigate other possible root causes instead of the simple fix to "Timestamp Optional" in the Admin panel. These costs could have been avoided if the API response had provided a clear error message explaining the reason for the failed uploads or at least suggesting that the error had occurred in the Analytics engine.How would you like the feature to work - The current API response should provide the user with feedback if the upload will fail for any reason related to known limitations on the file or report suite. Alternatively, the Admin panel could provide logs or another form of feedback showing whether previous BDIA uploads were successful or failed. At that time, it could check whether the Analytics engine processed all BDIA uploads to completion.Current Behavior - The current API response suggests a successful upload occurred even if the upload fails for reasons related to known limitations. Excerpt of API Response from 1 upload:[status_code] => UPLOADED[processing_log] => Processing complete: 875 rows will be submitted. No invalid rows.

daniellereischNew Participant

Improve Anomaly Detection UIDelivered

I am loving Anomaly Detection and Contribution Analysis. As a feature this is such a helpful thing to have, and I know we'll engage with it often. However, I've noticed there are a few hiccups / usability issues that could improve use of the tool:  Sometimes I can't click an anomaly in the timeline and have it show below, and it's not entirely clear whyWhen I open up the Analysis Queue (which is a little hard to see, honestly), the middle anomaly detection report is only partially fluid to that menu, so although the graphs change in scale, the date-range selector gets partially covered. I think that could get simplified to a single calendar icon so it all fits on-screen (1280 width here)When there are no anomalies found, I would really like to see that metric/those metrics trended so I can validate for myself / check if I should be more sensitive witih my training period. I realize that doesn't fit with the current user flow (see anomaly, click, then see metric trended with anomalies.) However, when looking at a metric that gets counted millions of times a month and certainly has inorganic shifts, it's hard to believe when only an error message is returned and no data. Then I need to pop over into a metric report to observe highs and lows, and ruin my flow. In contribution analysis, I really wish I could rename completed reports to something else, as I have to hover and peck to find ones that have already been completed (and, if I change my dimension criteria but look at an anomaly on the same metric and same day, it's impossible to tell them apart.)Sometimes I hover over an anomaly in the timeline and its caption shifts to the left or right (but it always looks like the caption is pointing to the right)I would REALLY love to use calculated metrics in here! This is a great start, but calculated metrics are where you really see shifts in behavior.  Overall, though, I am very happy! Please continue to work on tools like this, that bring faster insight out of our data!