What is Data Science?

 In data science

In a broad sense, it is a series of capabilities and specific use of techniques that help extracting insights, information and conclusions about data.
Data Science is the analysis, cleansing and preparation of everything related to data, it revolves around the combination of statistics, mathematics, programming, problem-solving, capturing data in ingenious ways and the ability to look at things differently.

What are its applications?

Mostly, there are three ways of working with the knowledge that analysis of data provides:
A) Internet search engines: The creation and use of algorithms to deliver best results for search queries in a fraction of seconds.

B) Digital Advertisements: Data science algorithms are used by the whole marketing industry to create everything, from display banners to digital billboards. This is why digital ads are getting higher CTR instead of traditional advertising.

C) Recommender systems: A lot of companies use recommender systems to promote their products and suggestions in accordance with the user’s demands and relevance of information. The recommendations are based on the user’s previous search results. Think on Spotify’s “Discovery Weekly” playlist that works with previous data shared by your listening habits.

Can I become a Data Scientist?

There are a few standards of preferences in the field that can help you get involved in the area. To cite some facts:
-Education: 88% have a Master’s Degree and 46% have PhDs
-In-depth knowledge of SAS and/or R: For Data Science, R is generally preferred.
-Python coding: Python is the most common coding language used in data science along with Java, Perl, C/C++.
-Working with unstructured data: It is most important that a Data Scientist is able to work with unstructured data be it on social media, video feeds, or audio.

Source: https://www.simplilearn.com/data-science-vs-big-data-vs-data-analytics-article

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