Engineering insights

Practical guidance on data, cloud and AI

Read how we approach common engineering decisions, with links to relevant project experience.

UTIS perspective / Data platforms

How to reduce data-processing costs without changing the results.

Repeated processing can increase cloud costs. Before changing compute capacity, check what each data job repeats, which outputs it must preserve and how you will compare the cost.

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UTIS perspective / Scientific AI

What to check before expanding a scientific AI workload.

A faster demonstration does not answer every deployment question. Confirm the reference result, test environment and remaining dependencies before deciding how to expand a scientific AI application.

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