What is Enterprise Search?
Learn the essentials of an enterprise search in order to improve the indexing and retrieval of your complex data.
Written by Morten Eriksen on
Learn the essentials of an enterprise search in order to improve the indexing and retrieval of your complex data.
Written by Morten Eriksen on
For many organizations and businesses a straightforward search engine in their digital platform is sufficient for their needs—searching and retrieving digital assets from their website for purposes like reuse and documentation.
Then why would you need an enterprise search solution? What is its formal definition? What are the main features? How does it differ from a regular search? What’s in it for you and your organization?
Enterprise search is a software solution where authorized users can retrieve content from several disparate sources.
Many large organizations in the enterprise class tend to have accumulated multiple data systems over the years and decades, resulting in a complex network both internally and externally to perform tasks and operations. These data systems may include databases, intranets, file systems, digital assets management, content management systems, and e-mail.
Depending on the enterprise search solution, the source data may be structured or unstructured, and the role of the enterprise search is to integrate and display said data in a clear overview. Additionally, many enterprise search solutions make use of access controls to define user rights and security measures.
In an enterprise search solution, content is processed through specific phases from source repository to the search results, with the following main ingredients:
Content collection most often consists of a push or pull model. A push model integrates the source system and the search engine by a connection that pushes new content directly to an API, which is important for real time indexing. A pull model gathers content via web crawling or a database connector, where the latter frequently looks for new, updated, or deleted content from the source.
Content processing converts incoming documents, which can be of many different formats, into plain text by using document filters. Many processes normalize content to improve recall and precision, with methods like stemming, lemmatization, synonym expansion, entity extraction, part of speech tagging, and tokenization. The latter splits content into lower-case (case-insensitive) tokens, which thereby functions as the basic matching unit.
Indexing stores parts of the resulting text in an index optimized for fast lookups, without storing the full text of the document. An index may include a dictionary of all unique words, ranking, and term frequency.
Query processing occurs when a user issues a query to the system, which consists of the entered term together with navigational options like faceting and page information.
Matching is performed by comparing the processed query to the stored index, and the enterprise search solution returns results that matches reference source documents.
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Enterprise search is often contrasted with both web search, which applies search technology to content on the open web—and desktop search, which applies search technology to content on a single computer.
Enterprise search often revolves around making connectors tailored to needs specific to the use case of your organization. Aside from the mentioned indexing of content from multiple repositories, enterprise search may include the following differentiating features:
Federated search transforms and broadcasts a query to disparate sources with the appropriate syntax, before merging and presenting the collected results in a unified and sortable format with minimal duplication.
Enterprise bookmarking is a collaborative tagging system for classifying structured and semi-structured enterprise data to be displayed in search results.
Entity extraction locates and classifies elements in text into predefined categories, like names of persons, organizations, locations, time and date, quantities, percentages, and more.
Faceted search is a technique allowing users to narrow down search results by applying filters based on faceted classification of the items.
Text clustering groups comprehensive search results into real-time computed topics based on descriptions, titles, excerpts, and metadata—which compensates for the faceting problems of incompatible metadata across different repositories.
User interfaces can feature richer UI and be more complex in enterprise search to enhance productivity, in contrast to the simple UI of web searches.
Access control restricts access to the content based on individual user identities, and can be complex due to the many types of access control mechanisms for different content sources.
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An enterprise search solution is a powerful tool to index, search, and display content from across all your organization’s complex repositories in a fast, secure, and easily manageable way.
However, whether to implement enterprise search or not in your organization depends entirely on the use case. An important requirement is that your organization has a lot of data in different systems that needs to be made accessible. If not, your organization probably only needs a simple search, akin to web or desktop search.
While the advantages of enterprise search has been directly and indirectly pointed out already, CEOWORLD Magazine lists four more benefits:
Improved decision making is achieved by making important data, like financial reports and legal documents, easily available for executives—when they need it during critical deliberations.
Increased productivity means that employees spend less time searching for information in silos and sluggish search engines, and instead utilise an enterprise search to quickly retrieve what they need.
Better customer service can be achieved by two approaches in enterprise search, the first being an external implementation of the solution—letting prospects and customers search and find information themselves, in their own tempo. The second approach relates to customer support being able to find relevant information quickly to help customers.
Cost effectiveness is the crowning achievement of the three previous factors, by making the ROI gradually higher as time goes by after implementing the solution and training employees.
Additional source: AIIM
Enterprise search is a software solution where authorized users can retrieve content from several disparate sources.
In an enterprise search solution, content is processed through specific phases from source repository to the search results, with the following main ingredients: Content collection, content processing, indexing, query processing, and matching.
In contrast to most web and desktop search solutions, enterprise search often features indexed content from multiple repositories, federated search, enterprise bookmarking, entity extraction, faceted search, text clustering, user interface, and access control.
An enterprise search solution is a powerful tool to index, search, and display content from across all your organization’s complex repositories in a fast, secure, and easily manageable way. It can improve your organization's decision making, productivity, customer service, and cost effectiveness.
Morten is the CEO and co-founder of Enonic. He has extensive experience as an entrepreneur focusing on areas like business development, product management, sales, and marketing. He started a digital agency in 1995 and built his first CMS in 1997, then founded Enonic in 2000 where his mission is to accelerate digital projects using innovative technology.
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