Quick Summary: Azure Synapse gives freedom to design query on the basis of required terms using server less resources or dedicated resources. Synapse Azure manages petabytes of data like a SQL ware house and it offers services like cloud service, data ware house service and MPP (Massively parallel processing service). As shown in above diagram it joins with multiple inputs or resources and supports end to end analytics at same place like ingestion, explore and visualization.

Azure Synapse Analytics

What is Azure Synapse Analytics?

Azure Synapse Analytics is big data analytics which brings limitless data together like enterprise data warehousing to explore and manage heterogeneous data workload which is helpful in BI and machine learning.

What are the key capabilities of Microsoft Synapse Analytics?

  • Integrations with Microsoft technologies, Business intelligent and Machine learning.
  • Flexible to manage multiple resources, users and usage on a single dashboard.
  • Highly secured such as data encryption, automated thread detection and also secured column and row level even object level to protect sensitive data.
  • Multiple choices on language selection like, .Net, T-Sql, Scala, Paython etc.

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What are the main components of Azure Synapse Analytics?

These are the four key MS Azure Synapse Components.

four key components of Azure Synapse

  • SQL analytics: Ms Synapse SQL can manage multiple relational and non-relation data. We can use dedicated SQL pool to import big data using simple T-sql quires and it stores data with columnar storage in relation tables which helpful to enhance performance and also reduces cost of the storage.
  • Apache Spark: Apache Spark is a performance booster which is load the data in memory and in memory computing is very faster.
  • Synapse Analytics Studio: Synapse Analytics Studio is a web-based SaaS Tool so user can manage from one place like data integration, work flow of data in pipe line, create data, data analysing and reporting and data visualization. It provides feature like performance optimization and code debug.
  • Connectors for ingesting/integrating data from data sources: Synapse features 85 native connectors for integrating the most popular data sources to ingest all data into the data warehouse.

Benefits of Azure Synapse Analytics

  • Industry leading SQL which performs Dedicated and serverless resources and also having different options according to need which is beneficial for cost, performance and unplanned data management.
  • In Spark application .Net supports for Spark to reuse C# knowledge and .Net exiting code.
  • SQL and Spark can explore stored data lake files like CSV, JSON
  • Monitoring Data Flow activity without any code via pipelines.
  • Flexibility of heterogenous data management.
  • Highly secured in Cloud platform.

Conclusion

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