Smartlogic Semaphore Inc. makers of the world-class semantic platform Semaphore, today announced it has been positioned for the second year, as a Leader in the 2018 Magic Quadrant for Metadata Management Solutions. Smartlogic was also recently recognized in the July 2018 Magic Quadrant for Insight Engines.
“We’re pleased to be positioned in the Gartner Magic Quadrants again this year,” Jeremy Bentley, CEO Smartlogic. “As information continues to explode and markets, regulations, and industries evolve, organizations will need complete and precise information to tackle strategic business initiatives. To do this, they must deploy systems that leverage semantic platforms, AI and machine learning strategies that automatically analyze, create and apply rich metadata to improve the functionality of repositories, analytics, search and transactional systems.”
Gartner’s market definition/description of metadata is: “Metadata describes various facets of an information asset in order to improve its usability throughout its life cycle. Metadata management is about the organization’s management of its data and information assets to address use cases such as data governance, analytics and enterprise metadata management (EMM). It is important to note that this understanding of metadata goes far beyond just technical facets; it is used as a reference for business-oriented and technical projects and builds the foundations for describing, inventorying and understanding data for multiple use cases such as information governance or analytics.”
The Semaphore platform approaches metadata management from a holistic perspective. It leverages semantic models, rule-based classification and sophisticated semantic processes to result in precise, complete and consistent metadata that is:
- Transparent – completely auditable to support information governance and regulatory compliance.
- Accurate and complete – surfaces all evidence within an asset using NLP, sophisticated statistical techniques and machine learning.
- Comprehensive – relationships and synonyms in the model ensure that equivalences and differences in vocabulary are recognized and leveraged.
With Semaphore, organizations can identify the context and meaning of enterprise information to power information governance, drive sophisticated analytics and automate workflows. It improves the veracity of information by harmonizing and enriching assets, structured or unstructured, internal or external to the organization to gain insight and make key business decisions.
Source: Gartner, Magic Quadrant for Metadata Management Solutions, August 9, 2018; Guido De Simoni, Alan Dayley, Roxane Edjlali. For more details Gartner subscribers can visit: https://www.gartner.com/document/G00340701
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About Smartlogic
Smartlogic’sSemaphore is an enterprise-grade semantic platform that allows organizations to realize the business value of their information. By leveraging a common
vocabulary and sophisticated semantic techniques Semaphore:
- Enriches information assets with precise, complete and consistent metadata
- Extracts facts, entities, and relationships to drive analytics and workflows
- Harmonizes all information sources to gain business insight
Semaphore brings structure to the unstructured, scales to manage organizational volumes and supports industry-standard semantic vocabularies.
Semaphore’s model-driven, rule-based semantic approach solves complex business problems that traditional technologies cannot. It integrates into and enhances the capabilities of existing technology to improve time to value for new opportunities.
Global organizations in the energy, healthcare, life sciences, financial services, government & intelligence, media and publishing and high tech manufacturing industries use Semaphore every day to enrich enterprise information with context and meaning. Semaphore extracts critical facts, entities, and relationships to power case management, workflows and advanced analytics. It harmonizes different data types from disparate sources to create logical data warehouses with a true semantic layer.
