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Cloud Analytics 
Cloud analytics is a type of cloud service model where data analysis and related services are 
performed ...
In its view, any analytics initiative “in which one or more of these elements is implemented in 
the cloud” qualifies as c...
optimized for users working on mobile applications, with screens resized for varying device 
types. 
These products promis...
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Cloud Analytics

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Cloud analytics is a type of cloud service model where data analysis and related services are performed on a public or private cloud. Cloud analytics can refer to any data analytics or business intelligence process that is carried out in collaboration with a cloud service provider.
Cloud analytics is also known as Software as a Service (SaaS)-based business intelligence (BI).

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Cloud Analytics

  1. 1. Cloud Analytics Cloud analytics is a type of cloud service model where data analysis and related services are performed on a public or private cloud. Cloud analytics can refer to any data analytics or business intelligence process that is carried out in collaboration with a cloud service provider. Cloud analytics is also known as Software as a Service (SaaS)-based business intelligence (BI). Cloud analytics is primarily a cloud-enabled solution that allows an organization or individual to perform business analysis or intelligence procedures. These solutions and services are delivered through cloud models, such as hosted data warehouses, SaaS business intelligence (BI) and social media analytic products powered by the cloud. Cloud analytics services work like a typical data analytics service, providing similar features and capabilities. The only difference is that cloud analytics integrates some or all of the service models of cloud computing in delivering that solution. Although cloud analytics is mainly a SaaS-based solution, it can also be a hybrid cloud solution. For example, hosted or cloud data warehouses not only provide the infrastructure to store massive amounts of data, but they also allow data analytics/business intelligence software to retrieve useful information when and where it is required. Moreover, some solutions also may be delivered through Platform as a Service (PaaS), where the end users/organization can create proprietary data analytics software to run on the cloud storage infrastructure. Gartner defines the six key elements of analytics as: 1. Data sources 2. Data models 3. Processing applications 4. Computing power 5. Analytic models 6. Sharing or storage of results
  2. 2. In its view, any analytics initiative “in which one or more of these elements is implemented in the cloud” qualifies as cloud analytics. Gartner analyst Bill Gassman noted that vendors offering cloud-based technologies designed to support a single element refer to themselves as cloud analytics companies. Cloud Analytics is the future of analytics? In the last few months we have seen new products launched by IT majors that have the potential to greatly influence the fortunes of the Analytics and Insights business. IBM’s Watson Analytics and Salesforce Wave Cloud Analytics are two examples of new solutions/ platforms that have hit the market. We can rest assured that many more such offerings will be launched in the coming months. Big Blue launched its Watson Analytics: It is a natural language-based cognitive service that can provide businesses instant access to powerful predictive insights and cool reports. It will enable business users to upload data to their cloud. Once data quality is established, the user can input his/her requests via an interactive screen and in return obtain predictive insights and reports via visualization. Salesforce launched Wave Cloud Analytics: The new service is different from other approaches to analytics: its search based, with data stored in a schema-less fashion. This allows for rapid, iterative exploration by users who are in search of answers to questions. The visualizations are
  3. 3. optimized for users working on mobile applications, with screens resized for varying device types. These products promise to be game changers because the business user does not require the intermediation of modelers to build predictive models or coders to write the code for the models. Across industry verticals, they will empower business users to make well informed decisions with ease and speed. They hold the promise of greatly widening user base. While the platforms are slick, it remains to be seen how the market responds. Ultimately, the revenue performance will determine if they are successful. These products have not emerged overnight. It is obviously the result of powerful research / understanding of customer requirements backed by significant investments. Business user communities across industries and are asking it. References http://www.techopedia.com/definition/26516/cloud-analytics http://www.forbes.com/sites/benkepes/2014/04/30/suddenly-everyone-wants-to-be-in-cloud-analytics/ http://searchbusinessanalytics.techtarget.com/definition/cloud-analytics http://cloudtimes.org/wp-content/uploads/2013/11/cloud-computing_analytics.jpg http://www.business2community.com/cloud-computing/cloud-based-analytics-service-future-analytics- 01023466 http://www.informationweek.com/cloud/software-as-a-service/salesforcecom-unveils-wave-analytics-cloud/ d/d-id/1316581?image_number=1 http://img.deusm.com/informationweek/2014/09/1315769/Watson-Analytics.jpg

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