Big Data In 5 Minutes | What Is Big Data?| Big Data Analytics | Big Data Tutorial | Simplilearn

Summary

This script delves into the vast realm of big data, highlighting the staggering amount of data generated by smartphones and the internet every minute. It introduces the five Vs—volume, velocity, variety, veracity, and value—as key characteristics of big data. The script uses healthcare as an example to illustrate the benefits of big data, such as improved disease detection and reduced costs. It explains how frameworks like Hadoop, with its Hadoop Distributed File System (HDFS) and MapReduce, enable the storage and processing of big data in a distributed and parallel manner. The video also explores big data's applications in gaming and disaster management, emphasizing its potential to transform various industries.

Takeaways

• 📱 Smartphones generate approximately 40 exabytes of data per month, per user, which scales to a massive amount when multiplied by the global number of smartphone users.
• 🌐 The internet generates an astonishing amount of data per minute, with millions of activities across platforms like Snapchat, Google, Facebook, YouTube, and email services.
• 🔍 Big data is characterized by the five Vs: Volume, Velocity, Variety, Veracity, and Value, which help in classifying and understanding the nature of data.
• 🏥 The healthcare industry is an example where big data plays a crucial role, with hospitals and clinics generating large volumes of patient data that can be leveraged for faster disease detection and improved treatments.
• 🗃️ Hadoop and its ecosystem, including the Hadoop Distributed File System (HDFS), are frameworks designed to store and process big data in a distributed and efficient manner.
• 🔄 HDFS stores data in a distributed manner, breaking down large files into smaller chunks and replicating them across different nodes for redundancy and fault tolerance.
• 🔧 MapReduce is a technique used for processing big data by breaking tasks into smaller sub-tasks, which are then processed in parallel across multiple machines.
• 🎮 Big data analysis has practical applications in various industries, including gaming, where user behavior data can be used to improve game design and reduce customer churn.
• 🌪️ Big data was instrumental in disaster management during Hurricane Sandy, providing predictive insights and aiding in the preparation and response to the storm's impact.
• ❓ The script poses a question about the incorrect statement regarding HDFS, highlighting the importance of understanding the capabilities and functions of big data storage systems.
• 🎁 The video encourages viewer engagement by asking for opinions on the future impact of big data and offering incentives for participation in the form of Amazon gift vouchers.

Q & A

How much data does a single smartphone user generate approximately every month?

A single smartphone user generates approximately 40 exabytes of data every month.

What is the term used to describe the massive amount of data generated by billions of smartphone users?

The term used to describe this massive amount of data is 'big data'.

What are the five characteristics, or '5 V's, of big data?

The five characteristics of big data are Volume, Velocity, Variety, Veracity, and Value.

How much data is generated per minute on the internet according to the script?

Per minute on the internet, 2.1 million snaps are shared on Snapchat, 3.8 million search queries are made on Google, 1 million people log onto Facebook, 4.5 million videos are watched on YouTube, and 188 million emails are sent.

What is the role of the Hadoop Distributed File System (HDFS) in big data storage?

HDFS is the storage layer of Hadoop that stores big data in a distributed manner, breaking down large files into smaller chunks and storing them across multiple data nodes.

What technique does Hadoop use to process big data?

Hadoop uses the MapReduce technique to process big data, which involves breaking a lengthy task into smaller tasks and processing them in parallel across different machines.

How does the MapReduce technique contribute to the processing of big data?

The MapReduce technique contributes by enabling parallel processing of data, making the processing faster and more efficient by distributing tasks across multiple machines.

What is the significance of the 'Veracity' of data in big data analysis?

Veracity refers to the accuracy and trustworthiness of the generated data, which is crucial for ensuring the reliability of the insights and decisions derived from big data analysis.

How does big data analysis benefit the healthcare industry?

Big data analysis in healthcare can enable faster disease detection, better treatment options, and reduced costs by analyzing vast volumes of patient records and test results.

Which of the following statements about HDFS is not correct according to the script?

The incorrect statement about HDFS according to the script is 'HDFS performs parallel processing of data', as HDFS is responsible for storage, not processing.

How was big data utilized during Hurricane Sandy in 2012?

During Hurricane Sandy in 2012, big data was used for disaster management to gain a better understanding of the storm's effect on the east coast of the U.S. and to predict the hurricane's landfall five days in advance.

Outlines

00:00

📱 The Phenomenon of Smartphone Data Generation

This paragraph delves into the staggering amount of data generated by smartphones, which is approximately 40 exabytes per month per user. It emphasizes the sheer scale of data produced when multiplied by the global number of smartphone users, highlighting the challenges this poses for traditional computing systems. The concept of big data is introduced, characterized by the five Vs: volume, velocity, variety, veracity, and value. The paragraph provides an example from the healthcare industry to illustrate these concepts, explaining how big data can be harnessed for faster disease detection, better treatment, and cost reduction. It also introduces various frameworks like Cassandra, Hadoop, and Spark for storing and processing big data, with a detailed explanation of how Hadoop's distributed file system and MapReduce technique work to manage big data efficiently.

05:04

🔍 Applications and Impact of Big Data

This paragraph, although incomplete, suggests a continuation of the discussion on big data's applications and impact. It mentions the use of big data in gaming to improve user experience and reduce churn rates, as well as its role in disaster management during Hurricane Sandy in 2012, where it was instrumental in predicting the storm's landfall and taking necessary precautions. The paragraph concludes with a quiz about the Hadoop Distributed File System (HDFS), inviting viewers to participate in the comments section for a chance to win Amazon gift vouchers. It also encourages viewers to like, share, subscribe, and turn on notifications for new content.

Keywords

💡Smartphones

Smartphones are mobile devices that have computing capabilities and internet connectivity, allowing users to perform various tasks such as making phone calls, sending texts, and accessing the internet. In the context of the video, they are highlighted as significant data generators, creating approximately 40 exabytes of data per month per user, which contributes to the concept of big data.

💡Big Data

Big Data refers to the large volume of data, both structured and unstructured, that inundates a business on a day-to-day basis. It's characterized by the five Vs: volume, velocity, variety, veracity, and value. The video uses big data as its central theme, discussing its generation, challenges, and applications across various industries.

💡Exabytes

An exabyte is a unit of information used to describe a large amount of data, equal to one billion gigabytes. The script mentions that a single smartphone user generates approximately 40 exabytes of data per month, emphasizing the scale of data production in the digital age.

💡Five V's

The concept of the five V's is a framework used to describe the characteristics of big data. They are volume (size of data), velocity (speed of data generation), variety (types of data), veracity (accuracy and trustworthiness of data), and value (the usefulness of data). The video explains each V with examples from the healthcare industry.

💡Healthcare Industry

The healthcare industry is used as an example in the video to illustrate the application of big data. It discusses how hospitals and clinics generate massive volumes of data in the form of patient records and test results, which can be analyzed to improve disease detection, treatment, and reduce costs.

💡Hadoop

Hadoop is an open-source framework that allows for the distributed processing of large data sets across clusters of computers using simple programming models. It is highlighted in the video as a tool for storing and processing big data through its distributed file system and MapReduce programming model.

💡Hadoop Distributed File System (HDFS)

HDFS is the primary distributed storage system used by Hadoop applications. It is designed to store large data sets reliably across clusters of commodity hardware. The video explains how HDFS stores data in a distributed manner, ensuring data safety even if one machine fails.

💡MapReduce

MapReduce is a programming model and an associated implementation for processing and generating large datasets. In the video, it is described as a technique that breaks down lengthy tasks into smaller ones, which are then processed in parallel by multiple machines, making data processing faster and more efficient.

💡Parallel Processing

Parallel processing is a method in computer science where many calculations are carried out simultaneously. The video uses the example of MapReduce to illustrate how parallel processing can be used to process big data more quickly by distributing tasks across multiple machines.

💡Data Nodes

In the context of HDFS, data nodes are the machines where the actual data is stored. The video mentions that in HDFS, smaller chunks of data are stored on multiple data nodes, which contributes to the distributed storage and fault tolerance of the system.

💡Disaster Management

Disaster management refers to the organizational and community efforts to prepare for, respond to, and recover from disasters. The video provides an example of how big data was used during Hurricane Sandy in 2012 to predict the storm's landfall and take necessary measures, showcasing the practical applications of big data analysis.

Highlights

Smartphones generate approximately 40 exabytes of data per month per user.

5 billion smartphone users generate a massive amount of data, termed as big data.

Big data is characterized by the 5 V's: Volume, Velocity, Variety, Veracity, and Value.

2.1 million snaps are shared on Snapchat, 3.8 million Google searches, 1 million Facebook logins, 4.5 million YouTube videos watched, and 188 million emails sent per minute on the internet.

Huge volumes of data are generated in healthcare, with 2314 exabytes collected annually in patient records and test results.

Velocity refers to the high speed at which big data is generated.

Variety encompasses structured, semi-structured, and unstructured data types.

Veracity is the accuracy and trustworthiness of the generated data.

Analyzing big data in healthcare enables faster disease detection, better treatment, and reduced costs.

Frameworks like Cassandra, Hadoop, and Spark are used to store and process big data.

Hadoop uses Hadoop Distributed File System (HDFS) to store data in a distributed manner.

HDFS breaks down large files into smaller chunks and stores copies across different nodes for redundancy.

MapReduce is a technique used for parallel processing of big data.

Parallel processing allows for faster and more efficient data processing by distributing tasks across multiple machines.

Big data analysis in gaming helps improve user experience and reduce customer churn rate.

Big data was instrumental in disaster management during Hurricane Sandy, enabling better understanding and prediction of the storm's impact.

The Hadoop Distributed File System (HDFS) is the storage layer of Hadoop.

Smaller chunks of data are stored on multiple data nodes in HDFS.

HDFS does not perform parallel processing of data; that is a function of MapReduce.

Transcripts

we all use smart phones but have you

ever wondered how much data it generates

in the form of texts phone calls emails

photos videos searches and music

approximately 40 exabytes of data gets

generated every month by a single

smartphone user

now imagine this number multiplied by 5

billion smartphone users that's a lot

for our mind even process isn't it in

fact this amount of data is quite a lot

for traditional computing systems to

handle and this massive amount of data

is what we term as big data let's have a

look at the data generated per minute on

the internet 2.1 million snaps are

shared on snapchat 3.8 million search

queries are made on google one million

people log onto facebook 4.5 million

videos are watched on youtube

188 million emails are sent that's a lot

of data so how do you classify any data

as big data this is possible with the

concept of five v's

volume

velocity

variety

veracity and value

let us understand this with an example

from the health care industry

hospitals and clinics across the world

generate massive volumes of data

2314 exabytes of data are collected

annually in the form of patient records

and test results

all this data is generated at a very

high speed which attributes to the

velocity of big data

variety refers to the various data types

such as structured semi-structured and

unstructured data examples include excel

records log files and x-ray images

accuracy and trustworthiness of the

generated data is termed as veracity

analyzing all this data will benefit the

medical sector by enabling faster

disease detection better treatment and

reduced cost

this is known as the value of big data

but how do we store and process this big

data to do this job we have various

frameworks such as cassandra hadoop and

spark let us take hadoop as an example

and see how hadoop stores and processes

big data

hadoop uses a distributed file system

known as hadoop distributed file system

to store big data if you have a huge

file your file will be broken down into

smaller chunks and stored in various

machines not only that when you break

the file you also make copies of it

which goes into different nodes this way

you store your big data in a distributed

way and make sure that even if one

machine fails your data is safe on

another

mapreduce technique is used to process

big data a lengthy task a is broken into

smaller tasks

b

c

and d

now instead of one machine three

machines take up each task and complete

it in a parallel fashion and assemble

the results at the end thanks to this

the processing becomes easy and fast

this is known as parallel processing

now that we have stored and processed

our big data we can analyze this data

for numerous applications

in games like halo 3 and call of duty

designers analyze user data to

understand at which stage most of the

users pause restart or quit playing this

insight can help them rework on the

story line of the game and improve the

user experience

which in turn reduces the customer churn

rate

similarly big data also helped with

disaster management during hurricane

sandy in 2012. it was used to gain a

better understanding of the storm's

effect on the east coast of the u.s and

necessary measures were taken it could

predict the hurricane's landfall five

days in advance which wasn't possible

earlier

these are some of the clear indications

of how valuable big data can be once it

is accurately processed and analyzed

so here's a question for you which of

the following statements is not correct

about hadoop distributed file system

hdfs

a hdfs is the storage layer of hadoop

b

data gets stored in a distributed manner

in hdfs

c

hdfs performs parallel processing of

data

d

smaller chunks of data are stored on

multiple data nodes in hdfs

give it a thought and leave your answers

in the comment section below three lucky

winners will receive amazon gift

vouchers now that you have learned what

big data is what do you think will be

the most significant impact of big data

in the future let us know in the

comments below if you enjoyed this video

it would only take a few seconds to like

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