enterprise searchEnterprise search is the organized retrieval of data that span multiple content types and localities by employees, clients and business partners using customized search engines and content management systems. Properly implemented, enterprise search creates an easily navigated interface for entering, categorizing and retrieving data securely, in compliance with security and data retention regulations. Enterprise search software tends to be only as good as the quality of the data input into the database. Specifically, it's only as good the description of the data by the meta data. Meta data is, simply, data about data. If someone creates a sales presentation and uploads it to the corporate servers, unless the title of the file is exceptionally well written or the file is placed within a sensible organization of folders, only the author will know what the presentation contains, who it was presented to, and what is might be useful for. Meta data, however, will allow a user to find the presentation, assuming that whomever uploaded it into the system added the right keywords. There are a number of kinds of enterprise search, including local installs, hosted versions and search appliances, so called “search in a box.” Each has relative advantages and disadvantages. Local installs allow customization but require that an organization has the financial or personnel resources to continually maintain and upgrade the investment. Hosted search outsources those functions but requires considerable trust and reliance on an external vendor. And search in a box may offer no customization at all, though it may be considerably more inexpensive. Enterprise search software has increasingly turned to a faceted approach, allowing users to narrow down the search to gradually finer and finer criteria. This improves upon the keyword search many users might think of (the Google model) and the structured search model (think of the early Yahoo model.) In the case of keyword search, if you don’t enter the correct keyword or if records weren’t added in a way that considers what end users might be looking for, a searcher may struggle to find the data. Similarly, in a browsing model, unless the taxonomies created by the catalogers of an enterprise's information make intuitive sense to an end user, ferreting out the required data will be a challenge. Faceted search allows all of the data in a system to be reduced to a series of dropdown menus, each narrowing down the total number of results. Enterprise search is complex. Beyond the considerable challenges of data management for a large organization, aissues of security, compliance and data classification can generally only be addressed by a trained knowledge retrieval expert. That complexity is multiplied by the complexity of an enterprise itself, with the potential for multiple offices, systems, content types, time zones, data pools and the like. Tying all of those systems together in a coordinated fashion in a way that allows for useful information retrieval requires careful preparation and forethought. Finally, because of all of these factors, cost is a major issue. ROI, or return on investment, is paramount to most corporate officers. Enterprise IT managers will find no shortage of vendors to address these challenges, including the giants of the software industry like Oracle, SAP, IBM, Google and Microsoft.
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| Last updated on:
Aug 28, 2008 |
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