Big data, Artificial Intelligence and Data Science
What does it all mean?
October 11, 2017
What is “big data” exactly?
The expression “big data” refers to the immense quantities of data our societies are now producing, thanks to technological advances. In the past two years alone, for example, we have produced 92% of all the data generated since the dawn of civilization!
How is big data used?
Big data offers tremendous potential for a vast range of industries, from retail to transportation management, health care, agriculture, banking, human resources and lots more. But first we need to make sense of it all.
Artificial intelligence lets us make all this data “talk,” since computer systems are constantly getting faster at analyzing huge amounts of information. These systems simulate human intelligence, hence the expression “artificial intelligence.”
Key terms and concepts
Machine learning is a subdiscipline of computer science, aimed at giving computers the ability to learn. The goal is to develop algorithms that don’t follow a strict sequence of instructions, but rather make predictions or decisions based on data.
An algorithm is a map or the structure of a computer program.
Learning algorithms are those used for machine learning.
An artificial neuron is a mathematical and computerized model of a biological neuron. Like a biological neuron, it has “inputs” and an “output” and the ability to interact with other neurons. These exciting and inhibiting outputs (activations) are usually represented by digital coefficients.
Key terms and concepts
Data mining uses algorithms drawn from various scientific disciplines, like statistics, artificial intelligence and computer science, to build models based on data, identifying interesting structures or patterns using specific criteria so as to extract as much knowledge as possible. This is the approach used in data journalism, for instance, which made it possible to analyze the millions of confidential documents published in the “Panama Papers” affair.
Analytics is the discovery, interpretation and explanation of relevant trends in data. It is based on the simultaneous application of statistical methods, computer programs and operational research.
Operational research develops conceptual models for analyzing and controlling complex situations, allowing decision makers to assess the issues and make the most effective choices.