Geospatial data, open data, IoT, computational physics and streaming infrastructure metrics - working across varied areas, we see the simplicity of standard approaches struggling to translate to complex, messy, multi-domain problems. In industry, theoretical challenges combine in nonlinear ways and success metrics are rarely neatly defined. The focus on accessible, reusable, scalable data solutions in short timescales can be a huge hurdle to newcomers used to refined, well-understood patterns. Moreover, as the capability of software tooling and hardware surges, a static skillset quickly becomes irrelevant. This presentation will outline six key insights about industrial mathematics, to help surf that wave.
