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Data science is a powerful source of innovation and business value.
As investments pour in and new technologies emerge, what are the most relevant and important trends to look out for?
Best practices around tools, process and guiding principles for large-scale deployment are taking shape, allowing enterprises to solve Machine Learning at scale.
Finally quality has got the edge on volume. Smaller, simpler models are starting to be deployed with super-clean data to get great results.
As the demand for data science capabilities grows, it’s clear there’s not enough talent to go round.
Automated, low-code models that can be used by those without data backgrounds offer enterprises a way round - but at cost.
As the importance of ESG scores increases, enterprises will need to build a credible scientific process that has data science, artificial intelligence and machine learning at its core.
Companies will invest much more in turning that mountain of data into gold.
Advances in the power and accessibility of data science approaches means you can interrogate data to give a comprehensive appraisal of your customers and their experience with your company.
If you want to be competitive, you need to sort your data constraints, and that's where Mesh-AI can help. Identify the areas in your organisation that require the most attention and solve your most crucial data bottlenecks. Get in touch with us at firstname.lastname@example.org for a Data Maturity Assessment.
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