Big Data Analysis
We have developed a proprietary an Ecosystem to support the identification and implementation of innovative business solutions based on the “Big Data Approach”. Ours is a “Full Stack”
Ecosystem that addresses with a single integrated solution all features needed to realize advanced Big Data IT solutions.
Our IT efforts are therefore focused on the development of the full stack and of the missing components necessary to integrate the available ones. In addition to being a Big Data Full Stack Platform, our key differentiator is the application of a semantic approach to Big Data to obtain information enrichment that differs from most common solutions in the market. As we all know, information is also multilingual, covering many languages and scripts, in all of their complexities and challenges.
- Catch key properties, for example, names, numbers, places, dialects
- More than a thousend of different data types supported (text, audio, video, IoT)
- Native review of files
- Conceptual search independent from keywords
- Sentiment extractions
- Automatic correlation of separated entities with information
- Multi-language text analytics
- Secure and integrated on rights research
- High level customization and knowledge management
- Horizontal research across multiple and different repositories
- Semantic Analysis
- Automatic Taxonomy
- Conceptual Correlation
- Entity Extraction
- Machine Learning
Information Enrichment – It enlarges information with other pertinent data. It is possible to extract organization names from tweets and make tweets searchable by organization names.
Propelled Enterprise Search – An accurate and refined contextual search within internal and external data that allows to search for a brand and to obtain results including its competitors.
Knowledge Discovery – Reveal patterns, trends and connections without direct inquiries such as identifying original reasons of an attrition between a company and its customers in social media.