I tend to think of Time Series data as being several orders of magnitude larger than 23 million data points per week (38 per second) but now I can't seem to find a good definition of Time Series data. Anyone have thoughts on the rough threshold between event data and time series data? I think of arrays of hundreds/thousands of individual sensors that take 10 measurements a second as "different" than user generated data that is time-ordered.
We emphasize "event data" which goes beyond blanket monitoring. This is "big data" because what you're tracking could still happen at high volume and velocity. We leave the third V, variety, up to you - ultimately you will know your business best and can create and extend the data model you need. Making a backend code change to add a single event collection could immediately lead to millions of very rich data points!
I can certainly relate to the challenges of working on a big data platform intended to immediately satisfy varied customers...
But mainly I want to say I'm super impressed with the Google Analytics 'storification'. I can imagine the difficulties in bringing that level of quality to myriad data sources, but I'm excited to see you succeed!
The article explicitly says "Characters with the same name can exist on different servers, so the mind-boggling 3.8 million unique names found in the dataset was not expected."
The comments on the source point out the same mechanism that aims to keep the US from killing him could also been seen as incentivizing the US protecting him from people who want everything released right away.