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02.26.09 Improving Knowledge Worker Productivity  By Bill Ives While a theme of the enterprise 2.0 is transparency, often the maze of different platforms, repositories, and metadata structures makes finding the information you need difficult, if not impossible. I recently spoke with Josh Rosenthal, founder and CEO at iQuest, about his experience with one of the top 5 international pharma companies that was struggling with enterprise search and had found it easier to re-invent a needed compound that try to find the existing one somewhere within their terabytes of data. I have written about iQuest before (most recently - Extending Google Enterprise Search Through iQuest) and want to disclosure that I am a shareholder, but not an employee. It is a company that I have long believed in. Since that post, iQuest has completely revamped their product line to significantly improve its capabilities. Their reengineered software suite builds on the prior capabilities and extends them through a new software platform. The phrama company we talked about had given up hope of being able to search their multiple terabytes of data in multiple repositories, diverse platforms, and different metadata structures with one tool until they ran a proof-of-concept trial with iQuest. iQuest gave them the capability to better employee a "find within" strategy rather than the ‘build all over again" strategy they had previously used. Here's what the company's Associate Director for Worldwide Document and Collaborations Solutions said about the results of the trial. "I firmly feel iQuest has unique value, and takes an approach to enterprise search that is both novel and truly helpful in improving knowledge worker productivity. I sense that in less than 12 months your flagship product will be truly a breakout and market-changing event."
iQuest now enables users to discover hidden patterns and relationships within and across large sets of data. In the past, discovering patterns in unstructured data was extremely difficult. iQuest's approach to pattern recognition and matching combines a propriety data ingestion process with natural language processing, grammatical network analysis and Social Network statistical algorithms to create an accurate and fast data analysis process that delivers strong results across structured, semi-structured, and unstructured data. iQuest greatly reduces the amount on manual management than is often found in enterprise search engines. You do not need to set up taxonomies or other data architectures. iQuest now provide a hardware/software solution that allows you to plug and play. Its "Contextual Search" semantic analysis then automatically generates connections and interrelationships across enterprise data repositories. It enables you to leverage the index of your enterprise information without having to build and maintain knowledge models using controlled vocabularies, taxonomies, and ontologies. Continue reading this article. About the Author: Dr. Bill Ives is an independent consultant and writer who has worked with Fortune 100 companies in business uses of emerging technologies for over 20 years. For several years he led the Knowledge Management Practice for a large consulting firm.. Now he primarily helps companies with their business blogs. He is also the VP of Social Media and blogger for TVissimo, a new TV schedule search engine. Prior to consulting, Dr. Ives was a Research Associate at Harvard University exploring the effects of media on cognition. He obtained his Ph. D. in Educational Psychology from the University of Toronto. Bill can be reached at his blog: Portals and KM. He also writes for the FastForward blog and the AppGap blog. |
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