Abstract: Organizations are generating, processing, and retaining data at a rate that often exceeds their ability to analyse it effectively. The outcomes and results derived from these large data sets helps in decision making and are often key to the success of the organizations. This helps in understand how to solve hard problems and thus gain competitive advantage. It has started being impractical to analyse using traditional offline, read-only relational databases because the data is so voluminous and increasing day by day. New “big data” technologies and architectures, like Hadoop and NoSQL databases, have been introduced to better support the needs of organizations analysing such data. In particular, Elastic search is a way to organize data and make it easily accessible. It is a server based search on Lucene. It is a distributed full-text search engine explicitly addresses issues of scalability, big data search, and performance that relational databases were simply never designed to support. In this paper, I reflect upon my own experience with Elastic search and how it can help organizations to manage their highly voluminous data.
Keyword: Elastic search, Dashboard, TFS (Team Foundation Server), Elastic search index.
Title: Elastic search as Middleware Search Engine for Dashboards
Author: Dashrath Mane, Rajinder Singh Pabla
International Journal of Computer Science and Information Technology Research
ISSN 2348-120X (online), ISSN 2348-1196 (print)
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