Prediction & Decision Science
Data tells a story about the processes which generate it. If you understand the patterns and relationships which govern your data, you can make calculated guesses about things that you haven’t seen yet - such as tomorrow’s demand, or a new demographic group.
Decision science takes this principle even further: depending on your objective it aims to infer the best possible action in any given circumstance, real or hypothetical.
Exploratory Data Science
You may suspect that your data is valuable, but you might not know exactly what it is that you’re looking for, or quite how to exploit it.
Our data detectives use cutting-edge statistical pattern-recognition methods, along with common-sense business understanding, to unearth meaningful groups and relationships in your data.
If there is value hidden in your data, we will find it!
Technical & Human Due Dilligence
Interpreting data is riddled with pitfalls. In mission-critical situations, the risk of applying insufficient rigor can outweigh the potential benefits of getting things right.
We assist those buying in or setting up in-house Data Science initiatives by providing advice on best practices, along with thorough and uncompromising appraisals of technology, processes and personnel.
Building robust theoretical models is great, but that may be just one piece of the puzzle.
Our goal is to help you turn your data into maximum bottom line value, by assisting with everything from optimizing the way you acquire data, through to designing and deploying dashboards and scalable data-driven apps and integrations.
“ The power of Data Science comes from marrying cutting edge statistical methods and algorithms with uncompromising human curiosity and rigour. ”
Spatial & Temporal Data
The real world has inherent structure, which imparts natural constraints and freedoms on the data that it generates. In geography this structure is spatial. In financial markets it is temporal. In fields such as logistics both dimensions are critical.
Understanding these mechanics can help us to build more plausible and effective data-driven models.
Our expertise in the Environmental Sciences and Time Series Modeling give us a special advantage in problem areas such as:
Financial Risk Modeling
Some data is so deeply structured that it seems to defy any conventional analysis. Social Media and Web content are classic examples.
It is often described as being "unstructured" but this is misleading: unlike in a conventional database where the structure is fixed by design and only the content varies, the very information of interest is encoded in the structure.
Our expertise in Statistical Semantics gives us a unique advantage in this area. Relevant problems include:
Recommendation & Targeted Marketing
Fraud & Anomaly Detection