Regarding "external tables", aren't all Synapse Analytics tables stored in data lake storage?

You're right, there's a nuance to consider regarding "external tables" and data lake storage in Synapse Analytics. Here's a clarification:

Dedicated SQL pool tables: These are traditional relational tables stored within the dedicated SQL pool itself. They offer high performance, isolation, and control but incur resource costs.
External tables: These point to data residing outside the dedicated SQL pool, typically in Azure Data Lake Storage (ADLS). They offer cost-effectiveness and flexibility for accessing large datasets but may have performance limitations and security considerations.

Not all Synapse tables are directly stored in ADLS. Only external tables explicitly point to ADLS data. Dedicated SQL pool tables reside within the pool's own storage.
However, Synapse Analytics leverages ADLS extensively for various purposes:
- Landing zone: ADLS can serve as a landing zone for incoming data before being processed or loaded into dedicated SQL pool tables.
- Data warehouse staging: External tables can be used to stage data from ADLS before loading it into dedicated SQL pool tables for analysis.
- Large data repository: ADLS can store vast datasets accessed through external tables or other tools for Big Data analytics beyond dedicated SQL pool.

Cost-effective: You only pay for storage in ADLS, not for additional resources within the dedicated SQL pool.
Scalable: External tables can handle massive datasets efficiently without impacting the pool's performance.
Flexibility: You can easily access and analyze data from various sources stored in ADLS using familiar T-SQL queries.

In conclusion:

While not all Synapse tables reside in ADLS, the platform leverages ADLS as a core data storage and processing layer.
External tables bridge the gap between dedicated SQL pool and ADLS, offering cost-effective and scalable access to large datasets.