Data Science Vs Data Mining: Difference Between Data Science & Data Mining

Data Science Vs Data Mining: Difference Between Data Science & Data Mining

Welcome to the comprehensive guide to the differences between Data Science and Data Mining.

Welcome to the comprehensive guide to the differences between Data Science and Data Mining.

The vast universe of technology, along with its improvement and development, is now crowded with a wide array of new terminologies. Amongst them are different terms related to data. Data related terminologies and job offers came into existence when organizations and enterprises realized the profits they could make from the data they collected. 

The Burgeoning Data Needs Handling

Data is everywhere, and with every passing second, new data keeps getting added. Would it surprise you to know that data is doubling? A person who can study the data has the power to transform the basic tenets of individual-enterprise interaction.  A Forbes article predicts that by the end of 2020, for every human on Earth, there will be 1.7 billion new data every second. IBM speculated that approximately 2.5 billion gigabytes of information was created every day in the year 2012 alone.

Since you are here, it is but natural to assume that you are aware that data is multiplying rapidly and shows no signs of stopping. The consistent trend has led to the generation of numerous methods of processing and handling data with the two most prominent ones being Data Science and Data Mining.

Data Science Vs Data Mining

Aspirants and students looking for a career in the field should know the individuality and uniqueness of each. Before we get to the details, let us have a quick look at the differences. 

The Major Role:

Data Science derives insights from structured and unstructured data. It is a multi-disciplinary field used for qualitative analysis. It comprises of behavioural science, language processingdata visualizations, data mining, and statistics and unstructured data.

Data Mining analyzes data sets created from structured data to unearth anomalies and hidden correlations and patterns. 

It is used for extracting data and generating predictions models. It is a subcategory of data science. 

Understanding the domain:

Data Science is also referred to as data-driven science. It is a field or wide domain that is inclusive of the procedures of obtaining and analyzing data and gaining information from it. 

Data Mining is also referred to as data discovery. It is a method and technique inclusive of data analysis. The focus is on discovering usable information in a dataset and using it to unearth covered patterns.

data science data science vs data mining

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