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Big Data in the Cloud with Azure Marketplace Images


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Here are some of the trends that I'm seeing from customer looking to build Azure-based Cloud Big Data solutions using images from the Azure Marketplace

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Big Data in the Cloud with Azure Marketplace Images

  1. 1. ModernDataWarehouse • Hadoop as an ETL/ELT optimization engine • Integration of streaming engines for data ingestion • Lambda and Hybrid architectures that include multiple processing and storage layers DataLakes • A good starting point for an organization to enter into Big Data • Collect data points as files in a massively distributed file system for analysis, processing and warehousing AdvancedAnalytics • Real-time stream- based analytics • Machine Learning • Leverage statistics- based packages in R and Python for exploratory analysis • Uncover the valuable data points from Data Lake
  2. 2. Scale • Elasticity. Don’t engineer for worst- case scenario all the time. • Moving data to Azure means taking advantage of Microsoft’s bottomless storage and enormous compute resources. SpeedofDeployment • Customers want to take advantage of Azure’s ability to automate deployments • A huge advantage of Cloud Data solutions in Azure is to quickly spin-up & spin- down environments in dev/test, QA, production as well as pause & stop PolyglotEnvironments • Azure Data solutions are able to incorporate complex heterogeneous data environments that include a large spectrum of engine and storage options from RDBMS to NoSQL to Hadoop • Take advantage of the Azure Marketplace