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Difference between big data- predictive analysis and machine learning 

Today every Data Professional has to put up with a question, what is a difference between Big Data, Predictive Analytics and Machine Learning Are they overlapping fields or poles apart let’s break it down for you

Firstly, coming to

1) Big Data:

Big data encompasses all type of data that may be structured, semi-structured or unstructured

90% of today’s data has been generated approximately 3 years back

Big data is based on three fundamental pillars or 3 V’s

They are

  • Velocity

Velocity is nothing but the speed at which data is increasing it is predicted as a volume of data doubles every 2years

  • Veracity (Variety)

It is a type of data it can be a structure(Excel file or database) or unstructured (like image or Video file)

  • Volume

It is the amount of data which we deal with is the Volume

Sources from where we get Big Data are

  • Social networking sites
  • E-Commerce sites
  • Weather station
  • Telecom company
  • Share Market

2)Predictive Analytics

Predictive analytics is a type of Data analytics. Now you may think what is Data analytics?

Data analytics is a process of examining the data sets to draw conclusions about useful information they contain

There are totally 3 types of analytics in Data analytics

  • Descriptive
  • Predictive
  • Prescriptive

Coming to Predictive analytics it tells us what could happen it is mainly used to make a prediction about unknown future events. Predictive analytics uses many techniques from data mining statics modeling machine learning and AI to analyze current data to make a prediction about future

3)Machine Learning

Machine learning empowers the machines to think and act for themselves, in other words, we can say it enables computers to learn from patterns and behaviors and act accordingly Without any human intervention or without being explicitly programmed to do so It uses different learning models like ARIMA, Gradient Boosting, SVM, Neutral networks and many more.

How it works

Normally we write programs to solve problems But in Machine learning we write a program that teaches a computer how to solve a problem for example

Suppose we have predicted sales for next month then, in that case, We will machine learning model that uses past historical data learn about pattern and behavior of stores sales and finally predict for next month

An advantage of machine learning is it can learn continuously to improve accuracy like human and predict maximum accuracy

By reading about these we came to a basic conclusion that these are connected by Data but these don’t work

The difference between data science and predictive analytics and machine learning is Big data has contains data that can be used for analytics. Predictive analytics uses data mining statistics modeling and Machine learning to envision data. Whereas machine learning uses data patterns and behaviors to Predict the future.

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