What are the main opportunities and challenges when it comes to getting machine learning out of a small corner of your business and actually using it to generate business value at scale?
Sean is a data expert and consultant that has been in the industry for 25 years. He has seen the landscape evolve through what he calls the ‘three waves’ of data and analytics (first, data warehouse; second, data lake; third, federated & cloud-based).
Sean and Kyle get into the weeds on a wide range of topics, including:
- The Mesh-AI story
- Real-life statistics and experience about how many ML models fail to get into production
- Reasons why so many organisations struggle to get ML into production
- Discussion around whether sector matters
- Specifics that need to be considered with regards to Data Management
- The non-technical components that must be respected
- Identifying when an organisation is ready for ML
- Differences in what companies are doing or not doing, which determines their success
- An idea to what ML looks like over the next 3-5 years
Check out the episode here >
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