i'm own an e-commerce company with a subscription product. We have customer purchase and behavior data stored in S3, EC2, and AWS database.
We also have other data sources we want to combine: multiple merchant accounts, google ads, facebook ads, Google analytics, Google sheets, video analytics, zendesk, amazon connect, email marketing data, quickbooks, appended data, etc
I want to move it to a place (athena, redshift, bigquery + data studio?) were we can pull the data, merge data sources together, and start to analyze it.
Any suggestions on what would be the best choice for my use case?
Hello, I'm Muntasir Al Qawasmi
I would like to say, in general terms, that the use of what was mentioned, Google and Amazon are quick and innovative solutions, and if used, it is for backup copies.
But in the case of a large company and a large number of daily data, I recommend creating a special program using Python that reads the data and delivers as appropriate for your business policy
I have been helping clients design, build, and deploy data platforms for many years. Initially on premise, but now in the cloud. I think your choice of technology is less important than your chosen data architecture. I would focus on defining this data architecture first (i.e. to satisfy your requirements) and then looking at how the Azure, AWS, or GCP clouds could best satisfy your requirement. I would consider things like data ingestion, orchestration, modelling, and exploitation. The biggest challenges won't be technology, but thinkings like 1) how do you model the data to answer your questions and 2) how do you relate/join the various data sources. I hope this helps; feel free to pop in a call of you would like to delve into more detail or if you have any questions.
