- Learn AWS
- Architecture
- Data lake and analytics
Architecture pattern
AWS Data lake and analytics architecture
when questions are asked of history, not of live rows
Storage and query are separated. Everything lands cheaply in S3 in open formats, a catalog describes it, and query engines read it without a cluster running between questions. Analysts get SQL over years of data without touching the production database.
What it runs through
In the order a request or a record moves through it. Each one links to the page that explains it.
- Data FirehoseAmazon Data Firehose
- S3Amazon S3
- GlueAWS Glue
- AthenaAmazon Athena
- QuickSightAmazon QuickSight
Signals in a brief that point here
Phrases that, when you meet them in a scenario, mean this shape rather than another. They are the tell, and they are what an exam question is built around.
- “reporting”
- “business intelligence”
- “query historical data”
- “years of records”
- “must not affect production”
What it costs you
Latency is seconds to minutes. This is never the path for a page a customer is waiting on.
Every shape has one. A design decision with no stated downside is usually a decision nobody has finished making.
Learn the services in it
Shapes it is easily confused with
These run through some of the same services, which is exactly why a brief that fits one can look like it fits another.
Now build it from a brief
Reading a shape and producing one from a scenario that never names a service are different skills, and the exam asks for the second. The scenarios give you the brief; you draw the architecture and it is scored against what the brief requires.