Why do Data Science?
The data science reveals trends and provides information that businesses can use to make better decisions and create more innovative products and services.
First of all, it is necessary to learn computer programming. Among the most commonly used languages in Data Science are Python, R and Scala. However, the priority is to learn Python. For good reason, this language is the one that federates the largest community of analysts of data.
It is not possible to become a data scientist without a degree. Without adequate training, you will not be able to find a job. Indeed, recruiters and clients require a minimum training adapted to the responsibilities that will weigh on you.
Data Analyst. Data Protection Officer. Web functional project manager. Web technical project manager.
This technology is used to assist decision-making in business, but also allows the automation of certain tasks. It is used for anomaly or fraud detection purposes. Data science also allows classification, for example to automatically sort the emails in your mailbox.
In general terms, data science is the extraction of knowledge from data sets.
To define Data Science in the simplest way, it is about extracting actionable insights from raw data. This multi-disciplinary field has the main purpose of identifying trends, patterns, connections and correlations in large data sets.
The goal of Data Science is to exploit this data, to give it meaning. This discipline aims to browse vast “data lakes” in search of connections, trends, points of interest.