RED Data Science activity is focused on delivering Actionable Insight from data.
Using techniques such as Statistical Analysis, Artificial Intelligence & Machine Learning we uncover hidden insight in data that can be used to guide decision making. We work with customers’ existing data as well as sourcing new material.
The RED approach is as follows:
Understand customer’s business requirements;
Source data;
Assess data quality and completeness ;
Cleanse data;
Pre-process data;
Perform analysis using statistical and AI / ML techniques;
Report on results including visualization.
The above approach is frequently iterative and RED works closely with customers at all times to ensure projects continue to meet or exceed requirements and offer valuable insight.
Examples of delivery in this area include:
Analysis of operations and maintenance records to optimise vehicle availability;
System failure data collation and analytics;
Insight from historical data to inform modelling / digital twins;
Advanced insight from monitoring data such as HUMS (Health and Usage Monitoring System).
Another RED strength is in sophisticated, automated sourcing of Open Source Intelligence (OSINT). OSINT is freely available data from the internet and can be a rich source of insight. RED’s solution is a secure, web-based service to automatically and anonymously harvest, parse, clean, consolidate, visualise and explore open source data from multiple sources and in different formats, saving time, effort and cost.
As well as Data Science we can also deliver related software systems such as databases and mathematical models / digital twins.
