Exploiting the Potential of Data
Data represents a significant competitive advantage, but its potential is often not exploited. With the right strategy and having the relevant information available at all times and in the appropriate context, data is a game-changer for companies worldwide.
The exponentially increasing volumes of data and the increasing amount of storage options complicate data evaluation and provision.
Relevant data sources are available in the cloud and the company's own data center. The business-critical corporate data and information are distributed across many different resources, and an overview is hardly possible without appropriate tools. However, the advantages of some modern knowledge management solutions can often only be exploited if all data is available in one data location - for example, in a cloud environment. Doing so is difficult, especially for areas where confidential or sensitive data is processed, and extensive compliance requirements must be observed. Insight Engines, and the hybrid approach option to connect data sources, are designed to do just that. Intelligent and innovative knowledge management solutions combine enterprise search technologies with AI-based speech recognition methods and machine and deep learning to process enterprise data and deliver it to users in an on-demand and context-specific manner.
Thanks to hybrid operating models, it does not matter whether the data is available in a cloud environment or the company's infrastructure – because the Insight Engine semantically captures and analyzes all information from the source systems connected via connectors.
Data always stays where it is (data center, cloud). Mindbreeze InSpire indexes business-critical data with high compliance requirements from on-premises and cloud applications. The result is an efficient knowledge base (graph and index) that delivers context and user-specific views of corporate knowledge in response to search queries. The results display knowledge to the users in a "holistic view or 360-degree view" – efficient, compact, and quickly graspable.
Interaction: Understanding Queries and Extracting Them
People communicate in natural language, and it is precisely this interaction that Insight Engines replicate with enterprise data. They analyze and understand structured metadata and text content using innovative speech recognition technologies, especially Natural Language Processing (NLP) and Natural Language Understanding (NLU).
During a query, Insight Engines determine the specific authorizations or knowledge requirements tailored to each employee and align the results accordingly. In addition to the organizational chart, the system also considers contextual information such as the respective work step, location, or time. Using machine learning, in particular the neural network model (deep learning), Insight Engines analyze user behavior. Based on previous search queries, their intention, and interactions with hits, individual relevance models categorize results and display information in a context-specific, personalized, and proactive manner according to importance.
Company managers and employees can then receive a personalized knowledge base from the entirety of company data at any time. Insight Engines create an optimal basis for making strategic and operational decisions and identifying opportunities or risks earlier in the business process.
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