What is Data Science? Who is it essential for?
To explain Data Science in simple words: It is a study of where information is extracted from, what it represents and how it can be converted into a valuable source in the building of IT and Business approaches.
Data science is a field which is composed of statistics, mathematics, and computer science disciplines efficiently and incorporates techniques like cluster analysis, machine learning, visualization, and data mining.
In the past few years, Data Science has calmly spread to include organizations and businesses worldwide. It is widely used by astronomers, analytics, and research, geneticists, entrepreneurs as well as engineers.
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Role of a Data Scientist
A data scientist aims to transform data into knowledge, knowledge which is used to make rational decisions. They possess all three set of skills - Mathematics and Statistics, Machine Learning and Subject Matter Expertise. Patrons who are masters in all three skills are less in number. The three skills required for data science mastery are explained below:
Machine Learning
Machine learning is a subfield of artificial intelligence based on statistics. It involves machines learning how to complete tasks without being explicitly programmed to do so. This part is explained in details further.
Mathematics and Statistics
While everyone knows what math is, statistics is the study of data: how to collect, summarize and present it. The statistics part will be covered in details later on.
Subject Matter Expertise (SME)
In general, a domain expert or subject-matter expert (SME) is an individual who is a specialist in a specific area or topic. An SME should also have basic knowledge of other technical subjects too. In Data Science an SME Provides industry/process-specific context for what the patterns identified by the algorithms and models mean.
Such Individuals who master all three skills are also called as Unicorn Data Scientist. Despite how rare unicorn data scientists are they are rapidly growing in demand. Also, there doesn't appear to be any end in sight for the growth of this demand. As a result, in the very near future, this specific set of skills will be in high demand, whether you're a data scientist or applying data science practices to your current job role. The rarity of data scientists combined with their high demand leads to much higher salaries for data scientists and IT professionals with similar skills.
Data Science Blogs
Data Science website is a platform for data scientists who can explore varied sources of data, build algorithms and models, and deploy work seamlessly. It also manages a blog, in which the articles are written by professionals who are currently working as data scientists.
Kaggle is a platform for analytics and predictive modeling, which is turning data science into a sport. A Data Science blog and kaggle’s competition, No Free Hunch, discusses tutorials, news and expert interviews exclusively related to data science.
Data Science [at] Berkeley blog which is an information hub for data science followers, featuring events coverage, interviews, data science startups and other insights on information technology.
FlowingData finds different ways in which statisticians, designers, and scientists use visualization, analysis, and exploration to enhance their knowledge of data. The Flowing Data maintains a blog which presents concepts on data which support readers to understand the trends in a relationship, transportation and more.
Insight Data Science conducts a six-week fellowship program, which is a postdoctoral program for connecting academia with data science. This website runs a blog which gives readers updates on industry news, descriptive data analyses, latest happenings and engages professionals with tips in the areas of data science.
