Titlebook: Beginning Azure Synapse Analytics; Transition from Data Bhadresh Shiyal Book 2021 Bhadresh Shiyal 2021 Modern Data Warehouse.Data Lakehouse

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Synapse Spark,visioned Synapse SQL; the third option is Synapse Spark, which is based on Apache Spark. We discussed Synapse SQL in detail in the previous chapter. Now, let us discuss Apache Spark, or Synapse Spark, in detail in this chapter.

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Synapse Pipelines,a warehouse, or a data lakehouse. To meet these requirements, you will have to build data ingestion pipelines, which will bring data to your desired target location. In addition, once you have ingested the data, you will have to cleanse it, apply business transformations and validations, and aggrega

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Synapse Workspace and Studio,o the amalgamation of many tools and technologies in it. For example, it contains three different compute engines. It includes Azure Data Factory, which is an entirely independent Azure Service, as Synapse Pipeline. It also allows you to integrate Power BI reports. It allows you to connect to multip

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Synapse Link, from disparate source systems. Historically, source systems are business applications being used continuously to carry out various business operations. These source systems generate and store a large amount of data in various formats. If you try to generate business intelligence while these source

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Azure Synapse Analytics Use Cases and Reference Architecture,our journey toward using Azure Synapse Analytics. As mentioned in other chapters, Azure Synapse Analytics is an amalgamation of multiple tools and technologies, so it is a little difficult to understand its architecture and its core components. Therefore, we have picked up each of those core compone