How to Build a Cloud Data Platform Part 2 - ETL Processing

In part 2 of this 4 part series you’ll learn how to create Delta Tables, what is Delta Lake Time Travel, and last but not least we explore how to perform an Upsert operation on Delta table. At the end of each session, you will be given redemption codes for additional free Databricks self-paced training and/or demo notebooks for hands-on practice.

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[thomsondcruz]

1:13:55 use “with cube” in group by not in the select clause.

SELECT device_id, name, avg(heartrate)
from <table>
group by device_id, name
with cube

[bogoodski]

This is super informative. There are SaaS type products that seem to abstract many of these ETL tasks away via UI for pipelining. Well, claim to. Or, at least provide a means of doing data transformations in a "low code / no code" way. I'm skeptical. I'll keep watching these videos and learning :)

[TheSQLPro]

1:13:55 under the aggregation section you can see Cube but it's in the Group by Clause not the Select clause

[TheSQLPro]

Great session just like the last one. Thank you!

[thomsondcruz]

1:13:55 select device_id, name, avg(heartrate) from table group by device_id, name with cube

[namanbhayani]

Amazing, Thanks. Lots of things are clarified here.

[zeeshanmirza]

Where can I find Notebook ? Please share the link of the Notebook used in Demo

[chrispollock]

The Azure Data Factory example at 1:15:17 did not have anything to do with Databricks Delta.