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Digital Newsletter
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The Digitalisation World Video magazine contains the latest Zoom interviews with experts in the industry.
By Joe Baguley, VP & CTO EMEA, VMware.
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“Machine Learning (ML) can take an organisation’s digital transformation to new heights” — It’s a statement we hear time and time again, but in practice, it doesn’t achieve that warm and fuzzy turn-key transformation feeling the statement asserts. By Santiago Giraldo, Director of Product Marketing at Cloudera.
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By Axel Schmidt, Senior Communications Manager, ProGlove.
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Machine learning (ML) has been often touted as the big thing that can solve nearly every problem. ML hype has washed over all walks of life - from business to academia. However, it has caused tunnel vision as businesses try to apply machine learning to context where other solutions would work better. By Juras Juršėnas, Chief Operations Officer at Oxylabs.io
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By Santiago Giraldo, Director of Product Marketing at Cloudera.
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By Gaurav Bajaj, Vice President at Secondmind.
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Data analytics and ML in a multi-cloud enterprise. By Vinay Wagh, Director of Product at Databricks.
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By Rachel Roumeliotis, VP of Data and AI at O’Reilly.
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Building ML Models may be ‘Data Fun’ but using them to support the business is where the value lies. By John Spooner, Head of Artificial Intelligence, EMEA, H2O.ai.
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These days, data is viewed as the lifeblood of organisations. Gartner has been heavily focused on the importance of developing a data-driven culture in the past year, stating that: “Leaders need to cultivate an organisational culture that is data-literate and that values information as an asset.” By Matt Middleton-Leal, EMEA & APAC General Manager at Netwrix.
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By Eran Kinsbruner, Chief Evangelist, Perfecto (by Perforce).
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Machine learning is computationally demanding, not just in terms of processing power but also the underlying graph query language and architecture of the system. We look at how these challenges can be addressed with native graph databases. By Richard Henderson, Solution Architect, TigerGraph EMEA.
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