IOT & BIG DATA ANALYTICS

M1-R5.1 & CCC · Chapter 9: Overview of Futureskills and Cyber Security · 4 min read

Internet of Things 

  1. IOT stands for Internet of Things.
  2. It was developed by Kavin Asthon in 1972.
  3. IIOT-  Industrial Internet of Things
  4. Internet of things means when objects  are more Connected to the Internet rather than  people. 

The internet of things refers to the network of interconnected physical devices, vehicles, applications and other objects embedded with sensors, software and network connectivity, enabling them to collect and exchange data.

Components of IOT :-

  1.  Smart devices and sensors
  2.  Network Connectivity
  3. Data processing
  4. user Interface

Big data & big data analytics 

What is Data ? 

The Quantities, Character or Symbols on Which  operation is performed by a computer may be  stored and transmitted in the form of electrical  signal and recorded on magnetic, Optical or  mechanical Recording media. 

WHAT IS BIG DATA ? 

Big data is also data but in large size. 

It is a term used to describe a collection of data  that is large in size and yet growing with time 

Example – The BSE( Bombay stock Exchange),  Social media like Facebook , Instagram,  E-commerce platform like Amazon, Flipkart  etc. 

TYPES OF BIG DATA- 

1.)Structured – 

Any Data that can be stored, Accessed and Processed in the form of fixed format is  termed as structured data  

Example- employe table in Company data base . 

2.) Unstructured – 

Any data with no Order(unknown format ) is classified as Unstructured data. 

Example-  email,facebook 

3.)Semi-structured- 

semi structured data is information that does not reside in relational data but that  does have some Organised properties that make it easier to analyze. 

CHARACTERISTICS OF BIG DATA:

There are 5 major characteristics of Big data or 5 V ’s of Big  data- 

1.) Volume- The name itself is related to a size which is large. 

2.) Variety- It represents nature of Big Data ( Structured or  unstructured) 

3.) Velocity- It represents the speed of generation of data. 

4.) Veracity – It refers to the Accuracy of data. 

5.) Value - It refers to the benefits that big data can provide,  and it relates directly to what organizations can do with that  collected data. 

BIG DATA ANALYTICS: 

  • Big data analytics refers to the method of analysing huge  volume of Big data. 
  • It is the process of collecting organising and analysing a  large amount of data to uncover hidden patterns, marketing  strategies and meaningful informations. 
  • It helps an organisation to understand the information  contained in their data and use it to provide new  opportunities to include their business. 

TYPES OF BIG DATA ANALYTICS:

There are major 4 types of Big data analytics – 

1.) Descriptive Analytics 

2.) Diagonastic Analytics 

3.) Predictive Analytics 

4.) Prescriptive Analytics. 

1.) Descriptive analytics – 

This type of Analytics makes questions “what has happened?”

It analyzes the data coming in real time for insight and how to approach the future. 

2.) Diagonastic Analytics– 

It consists of asking the question “ Why did it happen?” 

Diagonastic analytics looks for the root cause of problems. 

3.) Predictive Analytics– 

It consists of asking the question “What is likely to happen ?” 

It uses past data in order to predict the future. 

4.) Perspective Analytics– 

It consists of asking the question “ What should I do ?”. 

It advises on possible outcomes and results to maximize the key business Matrix.