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Ronald Schmelzer, principal analyst, managing partner and founder of the artificial intelligence-focused analyst and advisory firm Cognilytica explains, Data science, machine learning and AI are central to analytics and other enterprise uses. Here's what each involves and how combining them benefits organizations.
Photo: Techtarget
Today's organizations are awash in data. Just a decade ago, a gigabyte of data still seemed like a large quantity. Nowadays, however, some large organizations are managing upward of a zettabyte. To get a sense of how much data that is, if your typical laptop or desktop computer has a 1 TB hard drive inside it, a zettabyte is equal to one billion of those hard drives.
How can organizations even hope to get any business value from so much data?...
Let's look at each one, plus the differences between them and how they can be used together.
Data scienceWhile data has been central to computing since its inception, a separate field dealing specifically with data analytics didn't emerge until many decades later. Rather than the technical aspects of data management, data science focuses on statistical approaches, scientific methods and advanced analytics techniques that treat data as a discrete resource, regardless of how it's stored or manipulated...
Machine learningOne of the hallmarks of intelligence is the ability to learn from experience. If machines can identify patterns in data, they can then use those patterns to generate insights or predictions on new data that they're run against. This is the fundamental idea behind machine learning.
Machine learning relies on algorithms that can encode learning from examples of good data into models...
Artificial intelligenceAI is an idea older than computing itself: Is it possible to create machines that have the cognitive ability of humans? The idea has long inspired academicians, researchers and science fiction writers, and it emerged as a practical pursuit in the middle of the 20th century. In 1950, computing pioneer and well-known code-cracker Alan Turing came up with a fundamental test of machine intelligence, which became known as the Turing Test. The term artificial intelligence was coined in the proposal for a seminal AI conference that took place at Dartmouth in 1956...
Differences between data science, machine learning and AIWhile data science, machine learning and AI have affinities and support each other in analytics applications and other use cases, their concepts, goals and methods differ in significant ways. To further differentiate between them, consider these lists of some of their key attributes.
Source: Techtarget
