Big Data, Search and Navigation
Full-Text Search & Faceted Navigation
EXALEAD customers use CloudView to search and navigate Big Data sources, including data warehouses, mainframes, and non-relational ('NoSQL') databases, with Web-style ease.
While information retrieval often takes a back seat to analytics in Big Data discussions, easy information retrieval is critical to getting value from Big Data. CloudView meets this essential need by enabling users to access what they need without complex SQL queries, BSON objects or Map/Reduce functions.
Instead, CloudView replaces complexity with a faceted navigation and natural language queries, combined with user aids like type-ahead query suggestions, auto-spelling correction and fuzzy matching. The result is a remarkably effective tool for searching and exploring extremely large data collections.
- Bring critical accessibility to Big Data
- Add valuable context to structured data
Multimedia content is the fastest growing type of user-generated Big Data content, yet it is the least accessible of all. Most multimedia information retrieval systems rely on metadata that is usually limited and inconsistent. CloudView breaks through this limitation by using text mining (including contextual annotation) and semantic processing tools to enable search and navigation of content inside multimedia files. These tools include technologies like speech-to-text transcription, content-based image recognition and audio features extraction, and in addition to conventional search and navigation, they enable capabilities such as search by similarity and auto-recognition of images and sounds.
EXALEAD CloudView provides out-of-the-box content recommendation capabilities, the ability to automatically push specific content based on business rules and user context and behavior. This feature is used for managing content priorities, and for upselling and cross-selling in ecommerce contexts. And CloudView is engineered to deliver this capability with sub-second responsiveness against massive data sets.