In these later years, concepts such as data science, big data, machine or deep learning have been heard non-stop. Even though, it is still a topic which most people are unaware of, as there doesn’t exist a generalized knowledge about it.
What is Data Science?
The term Data Science has been present for a long time, however, it was not until the 70s when it started to define approaches to processing data.
The study of data is, in general terms, what Data Science is about. It involves recording, storing, and analyzing data with the purpose of extracting useful information.
The goal of Data science, ultimately, is making effective decisions. Consumers generate great value data that companies use for getting to know its clients. Nonetheless, a disorganized interpretation of the data does not contribute to creating value. So, the need for data scientists is increasing.
Parts of Data Science
What is Data Science conformed by?
- Mathematics/Statistics: Implies collecting, organizing, analysing and presenting the data.
- Computer Science: It is about creating programmes and algorithms to record and process data.
- Business knowledge: Jobs related to data science are much more than just understanding the know-how. Apart from having technical skill sets there needs to be a great knowledge of the industry and the business problem to be solved.
The important factors that conform Data Science
Data Science key concepts
There are concepts that should be emphasized in the data world.
DATA MINING
The process used for collecting and storing useful data is known as data mining. This process allows companies to obtain information about clients and develop strategies. Through mathematical algorithms data is evaluated for helping make better decisions.
DEEP LEARNING
Deep learning is a subset of Machine learning used for processing texts or recognising objects or voices, as we can see when using Siri.
How is this possible? Deep learning is based on the use of artificial neural networks for solving daily problems. There are several layers that structure the neural networks: the first, capture the information, the following is in charge of the calculation and the last the information is getting projected.
MACHINE LEARNING
As a tool, machine learning is used for educating the technology (algorithms) allowing them to learn without being programmed, by themselves.
It should be emphasized that it is not a synonym of artificial intelligence, indeed machine learning is a branch of it.
ARTIFICIAL INTELLIGENCE
Programmes based on algorithms able to reason and imitate human behaviour. Amazon is a perfect example of a company that uses AI in its daily activity.
The multinational was an early adopter of artificial intelligence for enhancing the customer’s experience. Moreover, AI is especially used to understand the searches and the reasons behind them that users do. The final goal is to be able to provide designed recommendations.
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