Let your data do the talking.
Signal Hub is an end-to-end Big Data analytics platform for large enterprises. It accelerates the process of extracting insights and intelligence from large volumes of data, including data of different types and in different formats.
Signal Hub delivers unique value to data scientists and analytics professionals by compressing analytic development time and promoting understanding and reusability of existing analytic components, allowing organizations to more effectively meet the growing demand for usable Big Data insights across all business functions and employee levels.
To increase the business impact and lifetime value of analytics work, Signal Hub stores the intelligence that it synthesizes in the form of shared, constantly refreshed mathematical transformations of data. These transformations are called Signals.
Signal Hub revolutionizes Big Data analytics by reimagining the data stack, inserting a new construct called a Signal Layer. The Signal Layer is a repository for the synthesized intelligence that an organization creates in the form of Signals. It sits between an enterprise’s data layer and the people who need to use that data to understand business situations and make decisions based on that understanding.
The Signal Layer is not a static data repository but is instead a library that is constantly refreshed. It continuously extracts Signal values from raw data, stores the Signals, manages the flow of Signals within Signal Hub, and enables rapid sharing of this highly synthesized information throughout the business, directly into the enterprise applications and workflows that the entire employee base uses every day. It also uses machine learning techniques that create a continuous learning system, ensuring that Signals remain relevant and accurate. This learning capability enriches and adapts insights that help shape and reshape business decisions as data changes over time.
The Signal Layer represents the design philosophy that inspired Signal Hub and is the technical brain that empowers the platform. It puts the power of data science into the hands of all employees, not just data scientists, allowing anyone in any role to “manufacture” use cases and rapidly solve business problems. It is the construct that transforms data science from a discrete analytical project into a scalable operational capacity.
From multiple data sources...
...to relevant data set...
...to the core insight...
...shared across the organization at scale.
Key features and functionality
- Ingests data (structured, unstructured, semi-structured) from myriad internal and external sources
- Prepares data with automated workflows that accelerate data intake, perform initial quality checks, automatically profile data, cleanse and normalize data, and perform ETLT in a flexible manner
- Generates descriptive Signals via the Signal API, which enables the aggregation, analysis, and manipulation of data
- Generates predictive Signals via a wide range of analytic techniques, including those involving deep-learning neural networks
- Supports easy discovery, exploration, and use of Signals via a powerful and flexible semantic layer that feeds an intuitive, interactive Signal management system
- Allows analytic components and Signals to be used multiple times across use cases and organizational entities within the business, eliminating time-consuming and repetitive data preparation activities
- Delivers analytic intelligence via Web service APIs or batch transfer directly into execution systems and enterprise application systems
- Enables an end-to-end business process for testing and learning within a closed-loop IT environment
Key benefits for your business
Signal Hub’s proprietary technology enables enterprises to overcome what has become the primary obstacle to large-scale adoption of advanced analytics: solving the scalability challenge. The Signal Layer allows Signal Hub to deliver this scalability across two dimensions: throughput and data democratization.
Higher throughput means that your business generates a larger volume of high-quality data assets and distributes synthesized insight rapidly across the entire organization. With Signal Hub, businesses benefit from an agile analytics methodology that allows a seamless transition from development to production, increases reuse of pre-existing data assets, and creates a virtuous cycle of continuous learning, refinement, and process improvement.
Data democratization means putting powerful data science capabilities into the hands of analysts and business leaders who may not have much or any understanding of advanced statistics, quantitative modeling, machine learning, or predictive analytics. With Signal Hub, they can focus on rapidly making critical business decisions with a level of speed and accuracy not possible before.
Want to know more?
Want to know more?
Ready to see it in action?