Articles

What is Big Data, Data Mining and Data Analytics?

by Aarushi Sharma Human Resource Executive

Big Data is mostly digital unstructured data that today’s society tries to structure, unify, and gain insights. The amount of unstructured data grows exponentially, and the means to process them needs to be of higher complexity compared to data analytics tools focused on small data sets. Big Data implies data sets that are too large to store in a single computer’s memory and must be both stored and processed distributively. For the latter, new algorithmic distribution models are to be applied.

big-data-non-accessible Another problem working with Big data is that most of it is not openly accessible. A big chunk of today’s data are kept secured. See the open info index (related to government data only). Regardless of this, the remaining public data is still huge and falls under Big Data concept.

Data Analysis

Data Analysis is a heuristic activity, where scanning through all the data the analyst gains some insight (makes it useful info). Data Analysis leverages statistical methods to analyze aggregated or non-aggregated data.Analytics is about applying a mechanical or algorithmic process to find insights. For example, running through various data sets with a purpose of finding meaningful correlation between them. This takes the use of statistics and data science tools. Analytics are the result of analysis and the form of presentation of the analysis results; might imply prediction interest.

Data mining

Data mining (term coined in business world) is analyzing data for the purpose of discovering unforeseen patterns or properties. It makes messy unstructured data into useful info.

It is the computational process of discovering patterns in large data sets (involving Big Data abstraction) involving methods at the intersection of artificial intelligence, machine learning, and database systems.

Data mining closely relates to data analysis. One can say that Data mining is data analytics operating on big data sets, because no small data sets would issue meaningful analytics insights. Data mining, shortly speaking, is the process of transforming data into useful information.

Data mining is more rooted on the database (static, already stored data) point of view, whereas machine learning has been originated from a desire to make an Artificial Intelligence (AI). Classical algorithms that I would classify Data mining ones include: Apriori (finding associations), DBSCAN (finding clusters) and Decision trees.


About Aarushi Sharma Senior     Human Resource Executive

211 connections, 10 recommendations, 639 honor points.
Joined APSense since, June 6th, 2019, From New Delhi, India.

Created on Nov 12th 2019 06:58. Viewed 86 times.

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