Some clients have data-engineering teams, some chose to rely on us to integrate the core infrastructure required for data-driven decision making. We call this the ‘data backbone’ of any program that facilitates any on-going optimisation. If required, we help select the best in class technology, especially so-called extract, transfer and load (ETL) vendors, we do the integration; configure the instances, stabilise the APIs, configure data storage, data warehouses (and even adtech like Data Management Platforms), build single customer views, dashboards, etc. We are fundamentally, always trying to remove the technology burden for our clients to focus on the feedback required for model refining that delivers their competitive advantage.
We have experienced project directors on our team that have thought strategically about the architecture for major corporations and had to hack together simple
solutions to prototype projects. We’ve delivered at all ends of the spectrum, so our data coaches and project managers have the experience of both waterfall and agile methodologies in delivering infrastructure builds.
Our projects range from hacking together the absolute ‘minimum viable product’ to get an enquiry off the ground, all the way through to carefully designing an
architecture to be ‘best in class’ long before it’s launch to internal clients. This would include data governance policies, procedures for aggregating data, hashing or
obfuscation and other Personal Information protection. We observe strict security policies for our infrastructure. We also run our own automatic back-ups and private mirroring to ensure no setbacks in our analysis for clients.
Elegant solutions require deep technical understanding to simplify the operation by clients and our own team. Our machine learning, semi-automation technologies, data-preparation algorithms another pipeline techniques all serve to reduce time spent preparing data and maximise time spent optimising the model for or with our clients.
Some of the so-called ‘big data’ challenges we face require significant computational power and for this, we can call on distributed computing nodes available in Cambridge’s high performance computer centres, to compute significant datasets. We are independent of legacy guardians of customer or relevant data, such as agencies or technology vendors, so we are not compromised by any commercial
Finally, as part of our governance policies, we do not store client data, so we offer any of the models rebuild as logics installed or as downloads to your ETL platform or other repository.