Azure has made a point of prioritizing AI and analytics services, making it an appealing option for many looking to combine big data analysis and the benefits of cloud computing. With Azure, you can easily process massive amounts of data, both structured and unstructured, with real-time analytics and faster performance than you are likely to get with on-premise resources.
Whether you have a team of data scientists or just want to begin taking advantage of the insights big data can offer, read on to learn about what setting up big data analysis on Azure entails and a bit about some of the services available to you.
Creating a Solution on Azure
To build an effective big data solution, you must address data collection, storage, analytics, and visualization, among other things. These needs can be addressed exclusively with Azure services or through a combination of Azure services and third-party integrations. Through the marketplace, there are even fully-managed, pre-built big data-as-a-service options that you can run, such as Cloudera, Qubole, and Cazena.
Evaluation
Before you can select services, you need to evaluate your big data goals. You need to understand what data types you wish to include and how the data from those types will be formatted. ...
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