Data Analytics & Machine Learning

We routinely find and exploit the right data sources for our customers. This involves detailed data analytics to explore data, preparing selected data sets and then applying appropriate algorithms to exploit the insight that can be gained. To achieve this we have a dedicated team of data scientists who work with customer, commercial and publicly available data to solve problems.

Creative Data Science

By applying a systematic approach to data science, we can quickly find and evaluate data sources to see if they help in solving customer problems. However, while being systematic is the key to squeezing the most out of data and understanding its usefulness, an influential aspect of data science is creativity. By being creative, our data scientists can look at a problem and explore different ways in which it might be solved. This leads us to different data sets that may be of use, and different techniques which may bring better accuracy or insight, from statistical analysis through to machine learning and beyond.

Systematic Evaluation

Of course, creativity is important, but being systematic is crucial. By exhaustively evaluating each step of our process, we ensure that the right data sets are selected, that they are evaluated fairly, that the data is pre-processed correctly and subsequently that each algorithm which we apply is then compared on an equal footing. Ultimately this means that our customers have confidence in our solutions and that we can accurately detail the performance of the algorithms we apply.