Data Analysis for Potential Reach Using Elasticsearch

Data Analysis for Potential Reach Using Elasticsearch

Nikhil Chaudhari
ISBN13: 9781522521570|ISBN10: 1522521577|EISBN13: 9781522521587
DOI: 10.4018/978-1-5225-2157-0.ch012
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MLA

Chaudhari, Nikhil. "Data Analysis for Potential Reach Using Elasticsearch." Exploring Enterprise Service Bus in the Service-Oriented Architecture Paradigm, edited by Robin Singh Bhadoria, et al., IGI Global, 2017, pp. 178-187. https://doi.org/10.4018/978-1-5225-2157-0.ch012

APA

Chaudhari, N. (2017). Data Analysis for Potential Reach Using Elasticsearch. In R. Bhadoria, N. Chaudhari, G. Tomar, & S. Singh (Eds.), Exploring Enterprise Service Bus in the Service-Oriented Architecture Paradigm (pp. 178-187). IGI Global. https://doi.org/10.4018/978-1-5225-2157-0.ch012

Chicago

Chaudhari, Nikhil. "Data Analysis for Potential Reach Using Elasticsearch." In Exploring Enterprise Service Bus in the Service-Oriented Architecture Paradigm, edited by Robin Singh Bhadoria, et al., 178-187. Hershey, PA: IGI Global, 2017. https://doi.org/10.4018/978-1-5225-2157-0.ch012

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Abstract

Elasticsearch has become an attractive open-source search and analytics engine for use cases such as log analytics, click stream analytics and real-time application monitoring. As a service, Elasticsearch is made available by Amazon Web services, Searchly.com, Bonsai and many other websites as a hosted engine. This hosted Elasticsearch service is known as Elastic Cloud. The aim of AWS (Amazon Web Services) is to provide Elasticsearch as a service to users. These web services can implement Service-oriented Architecture. In the following chapter Potential Reach is aggregated using the server. Potential Reach is a metric that indicates the reach of an online activity like tweet or comment. This number helps media marketers track the success of the brand or company.

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