What are the tools required by a Data Scientist?
Data Scientist
The role of a data analyst is to analyze data so as to gain insights which play a key role in any company’s decision-making and progress. However, when the velocity and volume of data are too high, the role of a data scientist with expert skills is essential to sort out the unstructured data and to gather critical information from it. The data scientist cleans the data, analyze it properly, and creates new algorithms to get the necessary insights from it. The necessary tools used for these are Python, R, Hadoop, Spark etc. Click here to know more about data science course
Python language
Python is an interactive programming language and is very much preferred in Data Science due to its flexibility and the availability of modules and packages crucial for Machine Learning and Data Science. The sub-modules of Python such as Scikit and pandas too offer a lot of help in analyzing, visualizing, cleaning, deploying, and testing datasets.
Python is also a fast language in comparison with other traditional languages used in Data Science and is easier and more understandable. It is free from complicated syntax and focuses more on the programmer’s use and has become most favored for Machine learning as well as Data Science.
The name Python is from the name of Monty Python, which was selected by the creator Guido Van Possum to indicate the fun-to-use feature of the programming language. Obscure sketches of Monty Python can be observed in the Python code documentation and examples.
The general purpose nature and extensibility of Python have made it inevitable in the field of data analytics. Though not well-suited for statistical analysis, organizations which have already invested in the language started standardizing on it and extending it to their purpose.
R language
R is a software environment and programming language useful for statistical analysis, reporting, and graphic representation. Created by Robert Gentleman and Ross Ihaka at the University of Auckland in New Zealand, it is currently being developed by the core R Development team. It is available freely under the GNU General Public License. Pre-compiled binary versions are also provided for operating systems such as Mac, Windows, and Linux. The name R was given to the programming language based on the initial letter of the first name of Ross and Robert who were the authors and is also a play on the name of S language used by the Bell Labs.
R language is mostly used by data miners to develop data analysis. Data mining surveys, polls, and literature databases prove that the popularity of the language has increased substantially in recent years. The source code for R software environment is written in Fortran, C, and R itself.
R is all about data visualization and manipulation. Even though there are other high-level programming languages capable of implementing the functions and features of R, they all require more additional coding to do it. R includes every tool that a data scientist needs to evaluate and manipulate structured data.
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