bigdata

BIG DATA

CONTENT: Introduction Why big data is required Big data Big data facts Big data 3 V’s Why big data is important Examples where big data is used Analytics Approach to analytic development Analysis of data through senser. Analytics can help in Big data analytics Big data analytics in practice How big data is used in twitter to get patterns Human resource cost and risk of big data. Big data analytics tools and technology Conclusions references

INTRODUCTION :OLTP: Online

Transaction Processing (DBMSs)

OLAP: Online Analytical Processing (Data Warehousing)

RTAP: Real-Time Analytics Processing (Big Data Architecture & technology)

WHY BIG DATA IS REQUIRED ?

High availability of data.Increase in storage capabilities.Increase in processing power.

BIGDATA :Big data is a collection of data sets that

are large and complex in nature.

They constitute both structured and unstructured data that grow large so fast that they are not manageable by traditional relational database systems or conventional statistical tools.

BIG DATA FACTS:We create 2.5 quintillion bytes every day.90% of world’s data was created in the last 2

years80% of world’s data is unstructured.Facebook processes 500 TB per day and

stores 30 petabytes of data.72 hrs of video are uploaded every minute.Twitter produces over 90 million tweets per

day.

BIGDATA: 3 V’s Bigdata is usually transformed in three dimensions- volume, velocity and

variety. Volume: Machine generated data is produced in larger quantities than non

traditional data. Velocity: This refers to the speed of data processing. Variety: This refers to large variety of input data which in turn generates

large amount of data as output.

EXAMPLES : 1. RETAILER COMPANY

2. TELECOMMUNICATION

3.E-RETAILER

WE CAN’T DEAL WITH SO MUCH INFORMATION

WHAT IS ANALYTICS :

APPROACH TO ANALYTIC DEVELOPMENT:

Identify the data sources . Select the right tools and technology to

collect ,store and aggregate the data. Understanding the business domain. Build mathematical models for the analytics. Visualize. Validate your result. Learn ,adapt,and rebuild your analytic model.

ANALYSIS OF DATA THROUGH SENSER:Senser data:

A senser is a converter that measures a physical quantity and transforms it into a digital signal .

Sensers are always on , capturing data at a low cost , and powering the “Internet of Things”

ANALYTICS CAN HELP IN :

WHAT IS BIG DATA ANALYTICS:Big data analytics is a process of :CollectingOrganizing and Analyzing of large sets of data (“ big data “) to discover patterns and Other useful information

BIG DATA ANALYTICS IN PRACTICE :

Etihad airways uses technology to harvest and analyze gigabytes of data generated by hundreds of sensors working insides its planes . This allows to monitor planes in real time, reduce fuel costs ,manage plane maintenance , and even spot problems before they happen.

BIG DATA ANALYTICS IN PRACTICE CONT’D:Many people use facebook to update their status ,share photos and “ like “ content.The Obama presidential compaign used all that data on the social network to not just find voters but to assemble an army of volunteers.

BIG DATA ANALYTICS IN PRACTICE CONT’D:One of India’s highest -rated TV shows aggregates and analyzes the millions of messages it receives from viewers on controversial issue like female feticide , caste discrimination and child abuse - and uses that data to push for political change.

Big data can detect bullying and gain new social insights:The researchers have developed a machine

learning algorithm that’s identifying more than 15,000 tweets per day relating to bullying .

They developed their model by feeding it two sets of tweets : one they had determined to be about bullying activity and another that was not.

Once the model learned the language identifiers of tweets containing bullying, it started identifying a huge amount of tweets from the Twitter firehouse and it also discovered time patterns.

How Big data works :

Conclusion:The availability of big data ,low -cost

commodity hardware ,and new information management and analytic software have produced a unique moment in the history of data analysis.

The convergence of these trends means that we have the capabilities required to analyze astonishing data sets quickly and cost – effectively for the first time in history .

These capabilities are neither theoretical nor trivial.

REFERENCES :https://www.youtube.com/watch?v=u5jWC89

xBzIhttps://www.youtube.com/watch?v=jujE79yE

u6Yhttp://labs.sogeti.com/big-data-can-detect-bul

lying-and-gain-new-social-insights/