True future building through Human Insight, Machine Learning and AI.



High-concept tech solving present-day problemsHigh-concept tech solving present-day problems

What is DataScience?

Smart business leaders are aware of the urgency to make the most of their data; to develop products, services and operational practices that are more productive, personalised and profitable. However, due to overlapping terms such as Data Science, AI, Machine Learning, Azure Analysis, Blockchain and many others besides, it’s increasingly difficult to pin-point the 'how' and 'why' they should be looking to develop their services – if many business leaders and industry professionals were asked to define each term, you would get many different answers. 

Our DataScience service is dedicated to demystifying the high-concept terms and applying these innovative solutions to modern day problems. Often businesses do not need to invest in an entire Data Team, but need to understand more about the potential of their data and how to leverage AI. As the barriers to using these technologies become lower, it will be the people who ask the right questions of data that deliver true innovation. 

Our DataScience practice is embedded within cloudThing, who integrate with our wider Development, Design and Business Architecture teams to design tech solutions at the vanguard of possibility to deliver measurable success, quickly. 

Our Approach to DataScience

Our DataScience principles are guided by the same 'Build Future' philosophy that covers everything we do at cloudThing. Transparency in our decision making, accountability for our actions and a dedication to long term value. 

To design our approach to a DataScience solution, our team will work with you to understand two key things - what is it you want to achieve, and what data is at your disposal to get started. From there, we can recommend a strategy and technology from the Microsoft stack to reach the desired outcome, as we would with any project. 

Our Data Scientists and Software Architects, pride themselves on designing solutions that are realistic, adaptable and robust enough to adjust to changing client or market demands. Whenbuilding a data modernization platform we ensure that all our solutions take advantage of existing tools within the market. 

Our Development team has the required experience to model, test and deliver a working algorithm and API, but when appropriate, we also look to take advantage of existing AI services which can hugely speed up both the development and testing process. 


AI is most effective when it’s grounded. We see DataScience as an evolution of existing development practices, and with the right mix of imagination and experience in how you put bleeding edge technologies together, you can create something magical.

Ed Yau- Solutions Architect at cloudThing




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