Member since: 2015
Application Area: Used for over 1 year
"I have tried to use InforSense (together with ClinicalSense) for over 1 year. The InforSense suite relies on outdated Java, so has to be run in a virtual box for starters. Following this, there is a complicated ontology to maintain with a few 'bespoke' data types like 'event' that oddly results in multiple instances of the same data being stored in tables, which is part of the reason updates and deletions of data then become so difficult. To update, load, or delete data then a series of what could be described as algorithms with a number of complex 'nodes' need to be created. These form the basis of tasks that can then be run to work with the data. Compared to writing SQL queries to accomplish the same thing, these algorithms, nodes, and tasks are vastly over-complicated and require specialist training and know-how to modify and use. Simply not a recommendable approach to our data needs. Wish we could get our money back."
• Integration of data and services from heterogeneous sources and architectures so that analytics can incorporate the most appropriate information
• Repeatable, auditable analytical processes to ensure decisions are being made consistently and systematically
• Domain specific extensions to enable the best analytics methodology for specific types of data or industry to be used; this includes domain specific components for text, image, genetics, cheminformatics, bioinformatics and patient-based analytics
• Embedding of applications into service oriented architectures, portals, dashboards, business process management systems, business rules engines, CRM systems and your own applications to enable the delivery of analytics to all users