What is ELEMENT™?

A cognitive being is capable of understanding data, and exploiting it. ELEMENT™ Cognitive Hub is tasked with understanding data, and performing knowledgeable actions based on it.

The Cognitive Hub is continuously monitoring information ingested by the gravity hub, in order to enrich it and provide productive insights from it. The Hub is fully automatic and is focused on proactively retrieving information and searching for missing information, based on configurable policies.

ELEMENT™ Cognitive Hub interprets domain specific data insights, configurable by domain experts, to map the organization knowledge using Semantic (Neural) Networks, capturing the various Entities, Topics, Relationships, Domain-Specific-Lingo, and other aspects of organization data perception.

Unlike conventional data processing, which can only handle neatly organized structured data, ELEMENT™ applies artificial intelligence to understand unstructured data which is the predominant data available today, and at the same time are harder to consume.

Relying on Natural Language Processing capabilities, and domain specific knowledge, the Cognitive Hub can read data written for humans, in its context. It does so by using grammatical rules, semantic correlation, and sentiment interpretation of texts.

All ingested data continues flowing through configurable processes, that iteratively enrich the data in context. Available data is retrieved using federated querying from internally and externally mapped repositories, and where ELEMENT™ identifies gaps in data, it triggers searches to complete it (e.g. seek person address from a high credential source, while identifying its current location from social media).

In parallel, the data is persisted in the system hybrid data layer, having factual information arranged in Knowledge Graphs, raw data maintained and indexed in big data repositories, transactional data maintained in a data-warehouse, etc.

As the knowledge graph evolves, ELEMENT™ applies analysis tools to further exploit the collected data. Geospatial and Temporal analytics and Behavioral Science are applied to identify patterns and anomalies in data, understand their implications and act upon them. Entity Analytics are applied on the ingested information to perform Entity Resolution and Disambiguation, names resolution, Relationship Resolution, etc., Predictive Analytics is applied to device policies for mitigating risks, and acting on opportunities, and at the same time, ELEMENT™ seeks to enrich the governing Ontologies, to assist in the organization learning process.

The Cognitive Hub continues to apply logic based policies on the information, and where it judges human intervention is required, based on the maturity of information, its relevance, its impact, etc., it can also escalate it to the internal or external data consumer, deemed relevant, by pushing it to the Discovery Hub.

The Discovery Hub is focused on the human interaction with the investigation process. The Hub facilitates the work of the analyst on the information processed by the system and, unlike the previous hubs, focuses on manually executed actions.

Information arrives into the Discovery hub actively via the Work Queue, which receives new and updated cases the Cognitive Hub decided to escalate for human intervention, documents ready for review, or alerts triggered as a result of enforced policies (rules, watch lists or risks).

Complete BPM-based Case Management embedded in this hub, governs the way data is flowing through the organization, who can access data, and how. A collaboration center further supplements the investigation process, allowing teams to discuss, share and disseminate data inside the organization and outside of it.

The Discovery hub also allows the analyst to interact with processed information, via an extensive set of analysis tools. The Hub offers a variety of big data visualization tools, rich set of search engines (including Full Textual Search, Visual Search Engine, Profile Search Engine, and more), integral analysis tools (such as Link Analysis, Geographic Analysis, Temporal Analysis), various Data Science tools, and more.

Using the Management Hub the organisation can configure ELEMENT™ to meet its unique requirements and address its specific challenges. The management hub combines a set of powerful tools that controls the entire data transformation process of the organization.

At the heart of the Management Hub is ELEMENT’ Big Data Science Platform, which enables the user to configure workflows for Big Data transformation. Each of the workflows can governs how the system acquires, ingests, transforms, analyzes & persists specific data sets. The output of each workflow can be a enriched data set, knowledge graph, answer to a specific business question, etc.

Other capabilities the management hub offers include Knowledge Graph manager – allowing to structure the building blocks of the knowledge graphs, including entities, relationships and attributes;  Policy Enforcement – a Business Rules Manager (BRM) allowing to configure and execute conditional policies; Orchestration – a Business Process Manager (BPM) allowing to configure and execute interactive business processes; Data Curation – allowing to train the system learning mechanisms; Document Parsing – allowing to train the system with capturing data from semi-structured documents; Decision Scoring – allowing to configure and evaluate weights; and a variety of additional domain specific modules.

Enabling the connectivity and seamless integration to any data or data source, with 10s of domain specific modules, hundreds of ready-to-run examples, a comprehensive range of Text Analysis and Machine Learning tools, the widest choice of advanced algorithms available, and a powerful set of effective modules, the management hub is the best tool on the belt of a Chief Data Officer, and the ultimate way to bring the organisation data to life.