Emails, project reports, quality documentation, process descriptions and presentations – a wealth of data accumulates on company computers every day. Often, the data is distributed across different systems or stored in cloud-based applications. Many companies additionally store their business-relevant data in so-called data lakes or big data hubs.
Whoever wants to take informed business decisions needs to be able to harness the data and information of their enterprise in order to analyze and interpret the information in a dynamic and targeted fashion. A prerequisite for this is finding out what kind of data is available in the company in the first place.
Search in Structured and Unstructured Data
Classic solutions such as document management systems often reach their limits when it comes to searching large amounts of data. Enterprise Search applications support companies in locating data across the enterprise. They are able to connect all relevant and heterogeneous data sources.
Universal View on Data
The search engine retrieves the information from the individual applications with so-called connectors and builds one central knowledge database – a search index. Users thus receive a 360-degree view of all important information and immediately recognize where the information is from. For finding information, users no longer need to know exactly in which data source the information was stored, and they no longer require to learn application-specific search mechanics.
A single user interface now provides users with the means of accessing all the information required for their daily work.
Professional enterprise search solutions offer much more than just merely tracking down information. Gartner has therefore coined the term “Insight Engine”. An Insight Engine supports users in interrelating and interpreting information. According to Gartner, insight engines understand natural language, are comprehensive and proactive. Enterprise Search solutions can easily cope with questions in the form of interrogative clauses, just the way users are familiar with in their daily work with Siri, Cortana or Google Now. In addition to supporting as many data sources as possible, the insight engine should also be able to provide users proactively with exactly the information they require for their research.
Content Analytic procedures support the extraction of the information gained from the documents and make them available to users for further analysis. The insight engine thus can identify proper names in documents and so makes it easier for users to derive relationships, for instance between a customer number and a quotation, an NDA, a registration for a webinar or a helpdesk ticket and further related documents. The search engine acts as the information cockpit which adapts and personalizes to the individual information requirements of each user, no matter where they work, in Purchasing or Sales. The system also considers integrated right schemes so that employees only get to find data in their search to which they have access rights.
The so-called Guided Search offers help in search processes with additional functionalities such as suggesting search terms or the possibility of setting filters. Users are thus able to verify at all times how they reached a specific search result. The Tag Cloud shows terms to users that topically match the search query. A Knowledge Graph provides a graphic and cumulated presentation of the search term, as is known from Google or Facebook.