Data Science is nothing but a improved mathematics that has been here for centuries. This is the skill or process used to gather information using improved method and process. Whether it’s a small Excel spreadsheet or 100 million records in a database, the goal is always the same: to find value. The main difference between the data science and traditional statics method which have been here forever is, Its not just to find the value of the data which is in hand but to predict the future trends.
Data Science is a newly developed blend of machine learning algorithms, statistics, business intelligence, and programming. This blend helps us reveal hidden patterns from the raw data, which in turn provides insights into business and manufacturing processes.
How to become Data Scientist?
Before starting every Data Scientist and those who aspire to become one must have the skills of a business analyst, a statistician, a programmer, and a Machine Learning developer. Luckily, for the first dive into the world of data, you do not need to be an expert in any of these fields but must have knowledge in the followings:
- Business Intelligence
- Statistics & Probability
- Programming languages like R / Python / SQL
- Machine Learning & AI
“R” Programming Language
Programming languages like Python and SQL has been there for long time, lets discuss something new, Which is “R”
R is a powerful language specifically designed for Data Science needs. It excels at a huge variety of statistical and data visualization applications, and being open source has an active community of contributors. In fact, 43 percent of data scientists are using R to solve statistical problems. However, it is difficult to learn, especially if you already mastered a programming language.