So many things can be measured continuously now - electricity, water consumption, temperature, ground moisture, population density, storage, plant growth, and so on.
As the hardware of this technology is getting cheaper and cheaper, organizations from all sectors are starting to collect massive amounts of such data and put them on dashboards. Exciting!
But:
- Is it always worth the trouble?
We should know what we are going to do with all that data - what difference will it make?
- Are we often missing the trees for the forest?
Instead of drowning in data, we should utilize machine learning to tell us what might be of interest in our data.
In this session, we'll discuss various examples, options, Dos and Don'ts. I'm curious to hear what opportunities exist out there and happy to share my experience.
My mission is that organizations can use data and digital automation to their full advantage. In particular, I believe this is an exciting time for SMEs and NGOs!
✅ I build lean & data-heavy software prototypes.
✅ I host workshops to rank data opportunities & discuss initial tech roadmaps.
✅ I boost tech team performance through review, best coding practices and agile/scrum.
✅ I form strategic (win-win) software & innovation partnerships.
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