Data Science: Data Science is a field that deals with extracting meaningful information and insights by applying various algorithms, processes., scientific methods from structured and unstructured data. This field is related to big data and one of the most demanded skills currently.
Data science comprises mathematics, computations, statistics, programming, etc to gain meaningful insights from the large amount of data provided in various formats.
Data Analytics: Data Analytics is used to get conclusions by processing the raw data. It is helpful in various businesses as it helps the company to make decisions based upon the conclusions from the data. Basically, data analytics helps to convert a Large number of figures in the form of data into Plain English i.e., conclusions which are further helpful in making the decisions.
Below is a table of differences between Data Science and Data Analytics:
|Feature||Data Science||Data Analytics|
|Coding Language||Python is the most commonly used language for data science along with the use of other languages such as C++, Java, Perl, etc.||The Knowledge of Python and R Language is essential for Data Analytics.|
|Programming Skills||In- depth knowledge of programming is required for data science.||Basic Programming skills is necessary for data analytics.|
|Use of Machine Learning||Data Science makes use of machine learning algorithms to get insights.||Data Analytics doesn’t makes use of machine learning.|
|Other Skills||Data Science makes use of Data mining activities for getting meaningful insights.||Hadoop Based analysis is used for getting conclusions from raw data.|
|Scope||The scope of data science is large.||The Scope of data analysis is micro i.e., small.||Goals||Data science deals with explorations and new innovations.||Data Analysis makes use of existing resources.||Data Type||Data Science mostly deals with unstructured data.||Data Analytics deals with structured data.||Statistical Skills||The statistical skills are necessary in the field of Data Science..||The statistical skills are of minimal or no use in data analytics.|