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When tomorrow comes
This morning, I spoke to a device in my room “is my flight later today on time?”. Having an affirmative answer, I ask ‘her’ to
Why do you need a Chief Data Officer?
The Chief Data Officer mission is to help set up a data strategy and coordinate the effort of the data engineering team. The CDO should
Why Data Science projects fail?
Brilliant ideas/algorithms are easy; execution is the hardest. Companies are racing for data scientists and eventually set them up for failure. For most organizations, data
Why DS projects fail
1: Lack of Resources to Execute Data Science Projects Data science is an interdisciplinary approach that involves mathematicians, statisticians, data engineering, software engineers, and importantly,
Some use cases of AI applications
In the supply-chain and logistics industry, AI is proving to be a game changer. McKinsey expects businesses to gain between $1.3tr and $2tr a year
9 Mistakes to avoid when investing in Data Science
1. AI is magic AI is a set of algorithms that learn from data using more or less sophisticated statistical techniques; It is not a