How does an Enterprise Search Tool Work
Today enterprises are facing the challenge of Big Data and the solution is investing in an enterprise search tool. But how does such a tool work? This article takes a closer look.
Big Data is one of the biggest challenges facing enterprises today. There is enormous volumes of data that is collected from various sources and there is the need to browse through this data to reveal insights hidden within. Also, there is the fact that a major share of this data is unstructured, which makes it impossible to decipher this data with the traditional methods of search. Moreover, this huge volumes of data need to be accessible to every department of the enterprise so that everyone can make use of it effectively.
The new age enterprise search tool is the answer to the challenges that organizations face today regarding deciphering meaning and analyzing unstructured data. So, what is an enterprise search tool and what makes it so efficient? How does such a tool work in analyzing unstructured data effectively? This article takes a look.
The Working of an Enterprise Search Tool
To understand how enterprise search tools work, one must understand the various steps involved, each playing an important role.
1] Collection: This is the very first step and as the name suggests, it involves collection of data that needs to be processed. This data can come from various sources, including websites, databases, emails, and directories. Either the search software is programmed to collect the data at regular intervals or data is fed to it.
2] Indexing: Once the content is gathered in the collection phase, the next step involves processing this content to create a searchable index that can be used to browse through the content. If required, this step also incorporates additional steps like content summarization and metadata extraction.
3] Query Parsing: This is the first process that takes place after the user interacts with the enterprise search tool. Once the user enters the query, the software uses Natural Language Processing (NLP) technology to encode the query to make the system understand it.
4] Query Engine: Once the query has been coded into the system or machine language, the software then runs the query through the database create beforehand, to find documents that match the query. It is important to note that the matching is not on the basis of keyword matching but using semantic search technology or semantics.
5] Post Processing: After the results are found, the post processing stage involves sorting these results on the basis of relevance or any other logic specified by the user. Clustering and categorization of search results are also incorporated if required.
6] Formatting: The final stage in the process, this stage involves the use of NLP by the enterprise search tool again to convert the results into human language and presenting it to the user in a pre-defined format.
An enterprise search tool is indeed a complex software, as it has to meet criteria like data security, regulatory compliance in order to be relevant and useful. One must be aware of the enormous volumes of data that is generated by enterprises to be able to understand the huge role played by the software in making it possible for enterprises to streamline the data and make it useful.
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ABOUT THE AUTHOR
Elise Lowry is a technical writer and a web entrepreneur with many years of experience. She regularly blogs about rising IT companies, path breaking IT solutions, current IT trends and much more. Understanding how technology affects the world we live in, is her subject of interest.