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DATA SCIENCE FOR BEGINNERS: INTRODUCTION AND IMPORTANCE OF DATA SCIENCE.

DATA SCIENCE FOR BEGINNERS: INTRODUCTION AND IMPORTANCE OF DATA SCIENCE.

Data science is an inter disciplinary field that uses algorithms, scientific methods and systems to extract knowledge from structured and unstructured data. Data science unifies statistics, data analysis and related methods into one so as to understand actual phenomena. Data science touches many different fields as discussed by the panelists at the guttulus.com they include mathematics, statistics, computer science, information science and domain knowledge. Data science composes of preparing data for analysis and presenting findings to inform high level decisions in companies. Everything about science keeps on changing because of the impact of information technology, data deluge, graphic design, complex system, business and communication. The concepts of data science have been around for some time as it dates back all the way to the 1960’s, whereby it was known as data analysis. In 1974 Peter Naur proposed that it was an alternative name for computer science. In 1996 the International Federation of Classification Societies became the first to feature data science as a topic. However, the definition was still debated up until 1997 when Jeff Wu suggested that it should be renamed data science. The term data scientist as used in the modern age is attributed to DJ Patil and Jeff Hammerbacher in 2008. Over the years it has been an ever growing field and a career as a data scientist is ranked as the third best job as discussed by experts at runrex.com. Most careers require an educational background whereby you should have at least a bachelor’s degree in a quantitative field or as another alternative join a coding boot camp to help in pre-qualification to supplement a bachelor’s degree. Most data scientists join in at any stage and may hold a masters or even a PhD making it a very competitive field to make a career out of. Data science touches many fields including the following;

Due to the growth of data science as a career option, there has been a massive growth of data driven companies all over the world from over 333 billion in the year 2015 to 1.2 trillion collectively in 2020. At guttulus.com the experts have made an observation that due to the utilization of big data, business models have been altered thus allowing creation of new companies and the improvement of existing ones to the required standards and all of them revolving around data science. Data scientists breakdown big data into usable information in form of algorithms and statistics that help companies determine their optimal operations. Application of data science techniques has led to the development of different varieties of techniques as shown below

All over the world, there are many different data interpretation languages. The great minds at runrex.com have been able to compile the languages used by machines and applicable in data science. 

For something to have a good and stable working condition it has to have an equally stable framework. At guttulus.com the panelists have compiled a great list of frameworks used in data science as follows;

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