Snowplow BDP

Data import across others platforms, productive data analytics and very effective for the activities tracking. The Drag and Drop interface is more helpful on easy navigation, easy to collaborate and monitoring on real-time capability is nice.

Nothing was detected as a problem on the system usability and also on getting started with the platform and the features.

It is very transparent as it is an open source software. We set up the validation rules, data modeling rules and data schema, so all in all it is very personalizable. During the onboarding process we got a lot of help from the success team, they were (and still are) really helpful.

You need some data engineers and architects to set up the data pipelines internally to on-premise datalake or to other marketing tools. It is not particularly Snowplow's fault, you just have to calculate with this issue if your company has strict security standards. It would be the same with other tools as well.

Having a good structure of events is sueful while not always required.

The set up with the different AWs services is kind of complicated and requires well oversight

Snowplow allows you to acquire such a great variety of data which is available to us in full detail and resolution. Additonally the whole ecosystem if stream and batch processing makes it a universal tool for a lot of enterprises

The learning curve is really steep if you start and read through all the wiki documentation. Good thing it exists, but i can see people being startled at first

I love the Data Structures functionality, and its relative ease to release new schemas in production. This cut our development and deployment time by 10x.

The infrastructure section could do with an upgrade. Currently, not sure what to make of it or how useful it is. Perhaps it would be great to see some health attributes / data metrics through it, to understand what is going on, a deeper level.