Based on our record, Funnel.io should be more popular than Google Cloud Dataproc. It has been mentiond 10 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
There are like a 100 services that will do that for you. Something like this. Source: over 1 year ago
Any digital marketers have experience working with single connectors for Google Data Studio? I really like the idea of plugging all the data sources into the ETL platform and having one connector for GDS. It appears funnel.io does this but it's far too expensive for us. Windsor.ai also looks ok but their pricing structure isn't ideal. Played around with Adverity as well but looking for something that's more plug... Source: over 1 year ago
From experience writing & maintaining custom ETLs in BigQuery, to paying/trying multiple data pipeline partners, to a sort-of middle ground like AirByte - this is not a plug - funnel.io has been the easiest and most cost effective by far. Source: over 2 years ago
You have to be careful with fb figures. Its well known in the industry that they arent accurate. With regards to funnel.io, if they are picking figures from FB then its also suspect. Source: over 2 years ago
The other platform (funnel.io) may use a different attribution window and/or it might not track across different devices (not sure here, never used funnel.io before). Source: over 2 years ago
I have also a spark cluster created with google cloud dataproc. Source: about 1 year ago
Specifically, we heavily rely on managed services from our cloud provider, Google Cloud Platform (GCP), for hosting our data in managed databases like BigTable and Spanner. For data transformations, we initially heavily relied on DataProc - a managed service from Google to manage a Spark cluster. - Source: dev.to / about 2 years ago
With that, the best way to maximize processing and minimize time is to use Dataflow or Dataproc depending on your needs. These systems are highly parallel and clustered, which allows for much larger processing pipelines that execute quickly. Source: over 2 years ago
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