Azure Synapse Link for Dataverse provides a continuous pipeline of data from Dataverse to Azure Synapse Analytics or Azure Data Lake Storage Gen2. Once the link is established, the service will export all the initial data as well as sync any incremental changes, enabling customers to glean near real-time insights from data sourced from the Microsoft Dataverse service.
Read MoreA data architecture pattern that brings elements of the data warehouse to the data lake, enabling a broader set of analytical workloads to coexist on a unified platform. The data lakehouse is not a new product or service, but rather an evolution of the data lake pattern, made possible due to recent technology breakthroughs that have brought warehouse-like capabilities such as ACID transaction support, schema evolution, and time travel to the data lake.
Read MoreHarnessing the ability to ingest, explore, prepare, transform, and serve data, historically meant that customers needed to provision, configure and maintain multiple services, suited for the different stages of the data lifecycle. Within the Microsoft ecosystem and prior to the availability of Azure Synapse Analytics, the usual suspects that would help facilitate such a set of capabilities would include services such as Azure Data Factory for data integration, Azure Databricks for big data, and dedicated SQL pools (formerly SQL DW) for data warehousing. With Azure Synapse Analytics, Microsoft has unified these capabilities under a single analytics service.
Read MoreData Flow is a new feature in Azure Data Factory currently available in limited preview that enables cloud based, code free, data transformations at scale, directly within Azure Data Factory’s visual authoring experience.
Read MoreDatabricks is an Apache Spark based analytics platform available as a first party service on Azure. Optimised for Microsoft’s various cloud services, Azure Databricks integrates deeply with Azure Active Directory, Azure Data Services, Power BI and more.
Read MoreApache Spark is a unified analytics engine for big data processing with built-in support for interactive queries (Spark SQL), real-time analytics (Spark Streaming), machine learning (MLib) and graph processing (GraphX).
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