I know we all have come across the term data science, but have you ever thought about what it is and its impacts on the tech world?

Well, today we'll dive deeper into what the field of data science entails

What is data science?

Data science is a tech-related field that uses various scientific methods to identify a problem in society, analyze it, collect meaningful data concerning the domain, clean the data, and structure it so that we can get some meaningful insights and knowledge to solve the specific problem.
Data analyst
This person specializes in the analysis of complex datasets from various sources and can extract information that can be used to make decisions in an organization.

What it takes to be a data scientist

The following are among the few key skill requirements for having a successful data science career:

Basic computer science knowledge

To be a data scientist, you need to have the fundamental knowledge of computer science which helps you to understand various concepts such as core maths, computer basics, database management and artificial intelligence.

programming

One also needs to understand programming languages such as Python, R and SQL which are mostly used by data scientists in their day-to-day life. The knowledge is practically applied in data manipulation and performing complex mathematical functions by use of simple libraries such as numpy in python.

Data collection and preparation

A data scientist must have solid skills in collecting and cleaning the collected data for easier analysis.This skill is key because clean data is easier to work with and also make accurate decisions from the data.

Data examining

The collected data should be examined to understand its flow and the overall characteristics which helps the data scientist to understand his data well.

Data analysis

In order to get insights from data,some data analysis skills must be applied by the scientist so as deep knowledge of statistics and mathematics is required.

Data modeling

Data modeling is the process of fitting and developing machine learning models that can predict possible outcomes and future patterns from the data. This requires one to have skills in the usage of various machine-learning models based on the type of outcome they need and the type of data present.

Data visualization

Visualization skills are key as they help us create visual presentations of findings and insights gained from the data. The tools used include Tableau and powerbi.

These are just but a few skills required to get you started in the field. Remember that the field of data is very wide and one requires to practice and learn daily so as to get better and always remember that Rome was never built in one day.