INNO-X provides you with the building blocks for making all your existing data available everywhere. These building blocks consist on one side of adapters for providing your data to INNO-X and on the other side interfaces for making your data available everywhere you need it. The same building blocks allow you to transform your data within INNO-X and restrict access to only those end users which are entitled to see the data. What makes INNO-X special is how the simple integration with your existing systems provides you with a real-time, robust, load-balanced and secure infrastructure for distributing and transforming your data.
For integrating with your existing systems INNO-X provides a broad range of adapters and in case such an adapter doesn’t exist yet, then INNO-X provides a simple and powerful interface for building custom adapters.
The data provided by the publisher sources that have been integrated with INNO-X can be processed by worker tasks to create a new source of transformed data such as blending FX rates from various market-data providers, calculate transfer pricing, filtering outliers, calculate client pricing by combining transfer prices with margin, etc.
The issues of how to parallelize computations, distribute data, and handle failures collude to complicate the original simple computation with large amounts of complex code to deal with these issues.
As a solution to this complexity, we designed a new abstraction that allows us to express the simple computations we have to perform but hides the messy details of parallelization, fault-tolerance and data distribution in a library.
Making all your data available to INNO-X doesn’t mean everybody should be allowed to see all your data. To restrict access to your data INNO-X provides adapters to various entitlement systems and an entitlement interface for building a custom entitlement system.
In INNO-X subscriptions define via their dependency hierarchy which data needs to be sourced. From the source initial data and update events will then drive the computations through the same hierarchy, but in the reverse order in real-time. This means that only that data is sourced that is required and only those calculations are made that are required. And if a subscription is unsubscribed, then all subscriptions in the dependency hierarchy will be unsubscribed. This allows you to save on data fees and on your electricity bill.
Large computations are parallelized by organising them into a hierarchical model of smaller computations, which will be distributed and synchronously executed by INNO-X on parallel threads, processes, computers and clusters. The performance of the complete infrastructure scales linearly with the number of compute nodes available.
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