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AZURE SYNAPSE INTERVIEW QUESTIONS

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Curriculum

Topic

01 - What is Azure Synapse Analytics and where does it fit in a modern data platform2:11
02 - What are the main components of Synapse (dedicated SQL pool, serverless SQL pool, Spark pool, pipelines)1:56
03 - What is Synapse Studio, and what are its hubs (Data, Develop, Integrate, Monitor, Manage)2:14
04 - How is Synapse different from Azure SQL Database2:10
05 - Explain Massively Parallel Processing (MPP) — how does the control node and compute nodes work2:05
06 - What is a DWU (Data Warehouse Unit), and how do you use it to balance cost and performance1:56
07 - What is the difference between a dedicated SQL pool and a serverless SQL pool2:01
08 - When would you choose serverless SQL over a dedicated SQL pool1:59
09 - What is a Synapse Spark pool and what workloads is it used for2:03
10 - Can you use PolyBase with a serverless SQL pool Why or why not1:51
11 - What languages and workloads does Synapse support across its engines2:09
12 - What is the role of Azure Data Lake Storage (ADLS) in a Synapse architecture2:07
13 - What are the table distribution strategies in a dedicated SQL pool (hash, round-robin, replicated)2:02
How do you choose a good hash distribution column1:57
15 - What is data skew, how do you detect it, and how do you fix it1:52
16 - What is a replicated table and when should you use it2:08
17 - What indexing options does a dedicated SQL pool offer, and when do you use clustered columnstore1:53
18 - What are the main ways to load data into a dedicated SQL pool — PolyBase vs the COPY statement — and which is2:03
19 - What is table partitioning in Synapse, how does it help, and what's the caveat with over-partitioning2:00
20 - What are result-set caching and materialized views, and when do they help2:02