Building the World's Largest Enterprise Data Warehouse with BigQuery (Cloud Next '18)

This talk, by one of the founders of the BigQuery team and a founder and current CTO of Looker, will make the case that BigQuery is not just another Enterprise Data Warehouse. It will show how BigQuery's unique properties follow from its technical architecture. The talk will announce new performance, security, cost, and manageability features. It will also show tricks and tips for getting more out of BigQuery. And finally it will show you how to push BigQuery to do things that you never thought were possible in a Data Warehouse.
DA215
Event schedule → g.co/next18
Watch more Data Analytics sessions here → bit.ly/2KXMtcJ
Next ‘18 All Sessions playlist → bit.ly/Allsessions
Subscribe to the Google Cloud channel! → bit.ly/NextSub
re_ty: Publish; product: Cloud - Data Analytics - BigQuery; fullname: Jordan Tigani; event: Google Cloud Next 2018;

[@muhammadquamberali4198]

Can you please share the algorithm used for encryption and decryption. Our bank needs to start sending those values now. So we need to know the algorithm. Like is it AES 256 or AES 128 etc?

[@ananthanarayanan8985]

I see the way you explain is great compared to what you did on 2015. Coming to the content, excellent stuff. Thanks

[@o3bvv]

In clustered vs non-clustered comparison, both queries state "Both of them state "This query will process 625G when run". But they report different volumes of actually processed data:
[8:30], non-clustered example: 1min+ for 625G *processed*
[9:00], clustered example: 12s for 22G *processed*
Is it a fair comparison? Or I am missing something?

[@jamief618]

see [17:30]

[@kalidsherefuddin]

Okay