E N D - U S E R I N S I G H T

Manish Jethwa , CTO , Ordnance Survey , the national mapping agency for Great Britain , shares insights into how the organisation ’ s data centre strategy supports its partnerships with government , businesses and tech giants .

Manish Jethwa , CTO , Ordnance Survey

We are fortunate to have our own data centre at Explorer House , which is complemented by using other providers like Microsoft ’ s Azure . This combination offers flexibility in data storage , ensuring resiliency , high availability and data bandwidth for processing and updating the OS National Geographic Database ( OS NGD ).

By leveraging both on-premises and cloud-based data centres , we can efficiently manage the vast amounts of geospatial data we collect .

This hybrid approach allows us to scale our operations as needed , providing the necessary infrastructure to support our data processing and storage requirements .

Additionally , it ensures that our data is always accessible and secure , enabling us to maintain the high standards of accuracy and reliability that our customers expect .

What role do technologies like Computer Vision and Machine Learning play in the storage , processing and updating of your geospatial data ?

We use Computer Vision ( CV ) and Machine Learning ( ML ) primarily for data processing , extracting and analysing features in collected imagery . These advanced technologies enable us to automate the identification and classification of various geographic features , such as buildings , roads and natural landscapes .

By integrating CV and ML into our workflows , we can update the OS NGD more frequently and share changes quickly with stakeholders , ensuring our data remains current . This automation not only improves the efficiency of our data processing , but it also enhances the accuracy and consistency of the information we provide . As a result , our customers benefit from up-to-date and

50 www . intelligentdatacentres . com