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Azure Synapse Analytics

Unified analytics: data warehouse, big data, and machine learning

⬢ 層級 2技術
高
薪資影響
5 個月
學習時長
困難
難度
12
職業
一覽

Azure Synapse Analytics integrates data warehousing, Spark, and ML. Mid-level data engineers earn $130-165k; seniors architect lakehouses and analytics platforms at $230-310k.

什麼是 Azure Synapse Analytics

Azure Synapse Analytics is a unified analytics platform that combines enterprise data warehousing (SQL), big data processing (Apache Spark), and machine learning into one service. It provides a single workspace for data engineers, analysts, and scientists to collaborate. Synapse integrates with Azure Data Lake Storage, Power BI, and AI/ML tools. - Unified platform: Data warehouse, Spark, and ML in one workspace

🔧 工具與生態
Synapse StudioSQL PoolsSpark PoolsData IntegrationPower BI IntegrationPipelinesNotebooksSQL ScriptsLinked ServicesMonitoring & Analytics

💰 各地區薪資

地區初級中級高級
USA$88,000$155,000$270,000
UK£64,000£113,000£196,000
EU€60,000€106,000€186,000
CANADACA$97,000CA$171,000CA$298,000

🎓 認證

Azure Data Engineer Associate (DP-203)
Azure Synapse Analytics certification

❓ 常見問題

What's the difference between Synapse SQL and Spark?
Synapse SQL is for structured data warehousing; Spark is for big data processing and unstructured data.
Can I use Synapse SQL and Spark together?
Yes, both share same metastore. Spark processes raw data, SQL queries refined datasets.
What's the pricing model?
SQL: pay per DWU-hour. Spark: per vCore-hour. Storage separate. On-demand SQL cheaper per query.
Can I connect Power BI directly?
Yes, native integration. Direct query or import; live dashboards update as data changes.
How do I handle data governance?
Column-level security, row-level security, data classifications, and audit logging.
What's the lakehouse pattern in Synapse?
Combine data lake (cheap storage) + warehouse (fast queries) using Delta Lake and unified metadata.

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