In 1936 Alan Turin envisions that the new field of computation will be required trained mathematicians to operate the modern machines. Since then we started a journey to simplify the way we interact with computers, at a point that now we use our fingers or voice to draw. But the skills required are changing, motivated by the data available and the need to answer more complex questions.
Many companies are realising that by using the new powerful tools we can answer very complex questions, making correlations with data available from different fields, and thanks to those powerful tools, the response only takes seconds which makes their adoption even more attractive.
To operate those new machines and tools a new skill set is required. The view of having computer programmers that could take requirements and develop useful software is not enough any more. Now is required an individual that can understand patterns, create models and then use computers to replicate human behaviour. The goal will be that machines will do what they are good at, evaluating algorithms at the speed of light, and using knowledge transferred to them to trigger actions, they will then help us to digest the immense amount of data available to produce answers.
This “new computer programmer” will need to have a bigger toolbox; one that holds tools from Statistics, to understand the probability of the phenomenon to decide how much data is enough and how valid are the assumptions; tools from Mathematics, to produce models that can be implemented in a computer, understand computational cost in terms of resource utilisation (Computational Mathematics); tools from Computer Science, to make decisions about architecture, languages, integrations and system design; tools from the Business field, to decode math and express his finding in a business appealing language and understanding business needs.
All of that applying a scientific approach, a method that will allow them to validate and track every decision made, every boundary, every step, to demonstrate we are in control and the results are the closest approximation to the best answer.
Data Scientist is the hero that will combine all those disciplines and knowledge in the right balance and his role a perfect combination of machine and human working together to solve problems and get answers. Previously we only use computers as a tool, now we will share our knowledge in the shape of algorithms and neural networks, so they can help us to make decisions. The thinking machines.
Join me in this series of posts in a journey to discover the toolbox of the Data Scientist, Where to get the knowledge, How to use the tools, Where to find more information, Interesting use cases and How you as a consumer of his work should be prepared. Keep tuned.
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