Big Data Analytics

Introduction

Analytics is defined as the process of extracting and creating information from new data by the process of filtering and bringing data into context

Types of Analytics

Descriptive Analytics

• This comprises of analyzing past data to present it in a summarized form which can be easily interpreted.

• The aim is to answer the question What happened

Diagnostic Analytics

• This is the analysis of past data to diagnose the reasons as to why certain events happened

• The aim is to answer the question Why did it happen

Predictive Analytics

• This comprises of predicting the occurence of an event or likely outcome of an event

• The aim is to answer What is likely to happen

Prescriptive Analytics

• This uses multiple prediction models to predict the various outcomes and best course of action for each outcome

• The aim is to answer What can we do to make it happen

A summary is given in Table below:

Analytics	What it Entails
Descriptive	What happened
Diagnostic	Why did it happen
Predictive	What is likely to happen
Prescriptive	What can we do to make it happen

Big Data

• This is a collection of datasets whose volume, velocity or variety is too large that it is difficult to store and manage it using traditional databases

Characteristics of Big Data

• Volume: The data is so large that it cannot fit on a single machine therefore need specialized tools.

• Velocity This refers to how fast the data is generated

• Variety: This refers to the forms of the data; structured, unstructured and semi-structured.

• Veracity This is how accurate the data is

• Value The usefulness of the data for the intended purpose