Data Science training skill sets

Posted by Nurul Islam on December 21st, 2018

What is Data Science?

               Data Science is a new branch of science which deals with the identification, extraction, and representation of information from various data sources to be used for advancing business purposes. It is a field of Big Data directed towards deriving meaningful information from a large amount of complex data. Data-driven science or data science is a combination of work in different fields such as statistics and computation to enable interpretation of data for the purpose of making strategic decisions.            

Requisite skill sets

A blend of skills in three major areas is required for a data scientist:

v  Expertise in Mathematics

The main requirement of a data scientist is the ability to view data with a quantitative eye. There are correlations, dimensions, and textures in data which can be expressed in a mathematical way. The methods of heuristics and quantitative technique have to be used to find solutions utilizing the available data. Finding solutions might involve building analytical models based on hard math while understanding their underlying mechanics is the key to success.

Even though statistics are important, knowledge of both branches of statistics such as classical and Bayesian statistics is important. Also, knowledge of linear algebra is helpful in machine learning algorithms and inferential techniques. Another popular strategy used to study the characteristics of a data set is SVD (Singular Value Decomposition), which is primarily matrix math and less of classical statistics. Overall, an in-depth knowledge of mathematics is helpful for a data scientist.

v  Hacking and Technology

First of all, hacking here doesn’t refer to breaking into computers, but the ingenuity and creativity to build things using technical skills and finding clever solutions to any problem. A data scientist utilizes technology so as to tussle with large data sets and complex algorithms and this needs very sophisticated tools. Knowledge of core languages such as Python, SQL, SAS, and R as well as Java, Julia, Scala, and others is essential. Just knowing the fundamentals of the language is also not enough. A hacker should be technically thorough with the ability to navigate creatively through tough technical challenges in order to make the code work.

Hence, such a hacker has to be an algorithmic thinker with the ability to crack messy problems and make them solvable. They need to comprehend the data control flows and analyze the Big Data to form a cohesive and acceptable solution.

v  Business / Strategy Acumen

The data Scientist has to be a tactful business consultant as well. They work so closely with the data and can learn from the data more than anyone else. That helps them to convert their observations to knowledge and strategic solutions to solve business issues. Thus, a competent data scientist can use major data insights to support and guide and be the spot-on business consultant.

This business acumen is as important as technical competence for a successful data scientist.  The ultimate aim is not the math, technology or data itself, but leveraging them all to strengthen capabilities and be a strategic business influence.

Do you think you have what it takes to be a successful data scientist? Click on the link data science training Singapore by ExcelR to enhance your skill sets and learn how to use them well.