SlideShare a Scribd company logo
1 of 18
BIG DATA
BY,
PRASHANT NAVATRE
20130737
CONTENTS
 Introduction
 The Need for Big data
 Characteristics of Big Data
 Volume
 Velocity
 Variety
 Sources of Big Data
 Processing Big Data
 Big Data Analytics
 Benefits of Big Data
 Drawbacks of Big Data
 Impacts of Big Data on IT
 Facts
 Future of Big Data
 India-Big Data
INTRODUCTION
 Big Data is high-volume, high-velocity and/or high-variety
information assets that demand cost-effective, innovative
forms of information processing that enable enhancedinsight,
decision making, and process automation
 But having data bigger it requires different approaches:
 Techniques, tools and architecture
 An aim to solve new problems or old problems in a better way
 Big Data generates value from the storage and processing of
very large quantities of digital information that cannot be
analyzed with traditional computing techniques.
 Like many new information technologies, big data can bring
about dramatic cost reductions, substantial improvements in the
time required to perform a computing task, or new product and
service offerings.
THE NEED FOR BIG DATA
• Growth of Big Data is needed
– Increase of storage capacities
– Increase of processing power
– Availability of data(different data types)
– Every day we create 2.5 quintrillion bytes of data;
90% of the data in the world today has been created
in the last two years alone
THREE CHARACTERISTICS OF BIG DATA
3VS
Volume
• Data
quantity
Velocity
• Data
Speed
Variety
• Data
Types
1ST CHARACTER OF BIG DATA
VOLUME
•A typical PC might have had 10 gigabytes of storage in 2000.
•Today, Facebook ingests 500 terabytes of new data every
day.
•Boeing 737 will generate 240 terabytes of flight data during a
single flight across the US.
• The smart phones, the data they create and consume;
sensors embedded into everyday objects will soon result in
billions of new, constantly-updated data feeds containing
environmental, location, and other information, including video.
2ND CHARACTER OF BIG DATA
VELOCITY
 Clickstreams and ad impressions capture user behavior
at millions of events per second
 High-frequency stock trading algorithms reflect market
changes within microseconds
 Machine to machine processes exchange data between
billions of devices
 On-line gaming systems support millions of concurrent
users, each producing multiple inputs per second.
3RD CHARACTER OF BIG DATA
VARIETY
 Big Data isn't just numbers, dates, and strings.
Big Data is also geospatial data, 3D data, audio
and video, and unstructured text, including log
files and social media.
 Big Data analysis includes different types of data
SOURCES OF BIG DATA
 Administrative Data
 Transactions
 Public Data
 Sensor Data
 Social media
PROCESSING BIG DATA
 Integrating disparate data stores
 Mapping data to the programming framework
 Connecting and extracting data from storage
 Transforming data for processing
 Subdividing data in preparation for Hadoop MapReduce
 Employing Hadoop MapReduce
 Creating the components of Hadoop MapReduce jobs
 Distributing data processing across server farms
 Executing Hadoop MapReduce jobs
 Monitoring the progress of job flows
BIG DATA ANALYTICS
 Examining large amount of data
 Appropriate information
 Identification of hidden patterns, unknown correlations
 Competitive advantage
 Better business decisions: strategic and operational
 Effective marketing, customer satisfaction, increased
revenue
BENEFITS OF BIG DATA
 Real-time big data isn’t just a process for storing
petabytes or exabytes of data in a data warehouse,
It’s about the ability to make better decisions and
take meaningful actions at the right time.
 Our newest research finds that organizations are
using big data to target customer-centric outcomes,
tap into internal data and build a better information
ecosystem.
 Big Data is already an important part of the $64
billion database and data analytics market
DRAWBACKS OF BIG DATA
 Security and Privacy issues
 Performance
 Data Representation
13
IMPACTS OF BIG DATA ON IT
 Big data is a troublesome force presenting
opportunities with challenges to IT organizations.
 By 2015 4.4 million IT jobs in Big Data ; 1.9 million
is in US itself
 India will require a minimum of 1 lakh data
scientists in the next couple of years in addition to
data analysts and data managers to support the Big
Data space.
FACTS
 FB generates 10TB daily
 Twitter generates 7TB of data Daily
 IBM claims 90% of today’s stored data was generated
in just the last two years.
 Decoding the human genome originally took 10years
to process; now it can be achieved in one week.
FUTURE OF BIG DATA
 $15 billion on software firms only specializing in
data management and analytics.
 This industry on its own is worth more than
$100 billion and growing at almost 10% a year
which is roughly twice as fast as the software
business as a whole.
INDIA – BIG DATA
 Big data analysis helped in parts, responsible for
the BJP and its allies to win Indian General Election
2014.
 The Indian Government utilises numerous
techniques to ascertain how the Indian electorate is
responding to government action, as well as ideas
for policy augmentation
THANK YOU.

More Related Content

What's hot

Big data analytics in healthcare
Big data analytics in healthcareBig data analytics in healthcare
Big data analytics in healthcareJoseph Thottungal
 
Big data Presentation
Big data PresentationBig data Presentation
Big data PresentationAswadmehar
 
Presentation About Big Data (DBMS)
Presentation About Big Data (DBMS)Presentation About Big Data (DBMS)
Presentation About Big Data (DBMS)SiamAhmed16
 
Big Data PPT by Rohit Dubey
Big Data PPT by Rohit DubeyBig Data PPT by Rohit Dubey
Big Data PPT by Rohit DubeyRohit Dubey
 
Big data by Mithlesh sadh
Big data by Mithlesh sadhBig data by Mithlesh sadh
Big data by Mithlesh sadhMithlesh Sadh
 
Big Data Characteristics And Process PowerPoint Presentation Slides
Big Data Characteristics And Process PowerPoint Presentation SlidesBig Data Characteristics And Process PowerPoint Presentation Slides
Big Data Characteristics And Process PowerPoint Presentation SlidesSlideTeam
 
Big Data - Applications and Technologies Overview
Big Data - Applications and Technologies OverviewBig Data - Applications and Technologies Overview
Big Data - Applications and Technologies OverviewSivashankar Ganapathy
 
Idiro Analytics - Analytics & Big Data
Idiro Analytics - Analytics & Big DataIdiro Analytics - Analytics & Big Data
Idiro Analytics - Analytics & Big DataIdiro Analytics
 
Big data analysis using map/reduce
Big data analysis using map/reduceBig data analysis using map/reduce
Big data analysis using map/reduceRenuSuren
 
Big data analytics with Apache Hadoop
Big data analytics with Apache  HadoopBig data analytics with Apache  Hadoop
Big data analytics with Apache HadoopSuman Saurabh
 

What's hot (20)

Big data analytics in healthcare
Big data analytics in healthcareBig data analytics in healthcare
Big data analytics in healthcare
 
Presentation on Big Data
Presentation on Big DataPresentation on Big Data
Presentation on Big Data
 
Presentation on Big Data
Presentation on Big DataPresentation on Big Data
Presentation on Big Data
 
Big data analytics
Big data analyticsBig data analytics
Big data analytics
 
Big data Presentation
Big data PresentationBig data Presentation
Big data Presentation
 
Presentation About Big Data (DBMS)
Presentation About Big Data (DBMS)Presentation About Big Data (DBMS)
Presentation About Big Data (DBMS)
 
Big data
Big dataBig data
Big data
 
Big data
Big dataBig data
Big data
 
Big Data
Big DataBig Data
Big Data
 
Big Data PPT by Rohit Dubey
Big Data PPT by Rohit DubeyBig Data PPT by Rohit Dubey
Big Data PPT by Rohit Dubey
 
Big data ppt
Big data pptBig data ppt
Big data ppt
 
Big data by Mithlesh sadh
Big data by Mithlesh sadhBig data by Mithlesh sadh
Big data by Mithlesh sadh
 
Big data analytics
Big data analyticsBig data analytics
Big data analytics
 
Big Data Characteristics And Process PowerPoint Presentation Slides
Big Data Characteristics And Process PowerPoint Presentation SlidesBig Data Characteristics And Process PowerPoint Presentation Slides
Big Data Characteristics And Process PowerPoint Presentation Slides
 
Big Data - Applications and Technologies Overview
Big Data - Applications and Technologies OverviewBig Data - Applications and Technologies Overview
Big Data - Applications and Technologies Overview
 
Big Data
Big DataBig Data
Big Data
 
Data analytics
Data analyticsData analytics
Data analytics
 
Idiro Analytics - Analytics & Big Data
Idiro Analytics - Analytics & Big DataIdiro Analytics - Analytics & Big Data
Idiro Analytics - Analytics & Big Data
 
Big data analysis using map/reduce
Big data analysis using map/reduceBig data analysis using map/reduce
Big data analysis using map/reduce
 
Big data analytics with Apache Hadoop
Big data analytics with Apache  HadoopBig data analytics with Apache  Hadoop
Big data analytics with Apache Hadoop
 

Viewers also liked (20)

Big data ppt
Big data pptBig data ppt
Big data ppt
 
Big Data ppt
Big Data pptBig Data ppt
Big Data ppt
 
Big data ppt
Big  data pptBig  data ppt
Big data ppt
 
Big data ppt
Big data pptBig data ppt
Big data ppt
 
big data overview ppt
big data overview pptbig data overview ppt
big data overview ppt
 
Big data ppt
Big data pptBig data ppt
Big data ppt
 
Ppt for Application of big data
Ppt for Application of big dataPpt for Application of big data
Ppt for Application of big data
 
Big data
Big dataBig data
Big data
 
What is Big Data?
What is Big Data?What is Big Data?
What is Big Data?
 
Big data ppt
Big data pptBig data ppt
Big data ppt
 
Big data ppt
Big data pptBig data ppt
Big data ppt
 
What is big data?
What is big data?What is big data?
What is big data?
 
Big Data
Big DataBig Data
Big Data
 
ICTA Meetup 11 - Big Data
ICTA Meetup 11 - Big DataICTA Meetup 11 - Big Data
ICTA Meetup 11 - Big Data
 
Hadoop Basics - Apache hadoop Bigdata training by Design Pathshala
Hadoop Basics - Apache hadoop Bigdata training by Design Pathshala Hadoop Basics - Apache hadoop Bigdata training by Design Pathshala
Hadoop Basics - Apache hadoop Bigdata training by Design Pathshala
 
Ets train ppt_big_data_basics_v2.0
Ets train ppt_big_data_basics_v2.0Ets train ppt_big_data_basics_v2.0
Ets train ppt_big_data_basics_v2.0
 
Splunk
SplunkSplunk
Splunk
 
Big data hadoop ecosystem and nosql
Big data hadoop ecosystem and nosqlBig data hadoop ecosystem and nosql
Big data hadoop ecosystem and nosql
 
Big data security the perfect storm
Big data security   the perfect stormBig data security   the perfect storm
Big data security the perfect storm
 
Presentación bigdata
Presentación bigdataPresentación bigdata
Presentación bigdata
 

Similar to Big data Ppt

big-data-8722-m8RQ3h1.pptx
big-data-8722-m8RQ3h1.pptxbig-data-8722-m8RQ3h1.pptx
big-data-8722-m8RQ3h1.pptxVaishnavGhadge1
 
BIG DATA & DATA ANALYTICS
BIG  DATA & DATA  ANALYTICSBIG  DATA & DATA  ANALYTICS
BIG DATA & DATA ANALYTICSNAGARAJAGIDDE
 
Analysis on big data concepts and applications
Analysis on big data concepts and applicationsAnalysis on big data concepts and applications
Analysis on big data concepts and applicationsIJARIIT
 
Big data seminor
Big data seminorBig data seminor
Big data seminorberasrujana
 
BigDataFinal.pptx
BigDataFinal.pptxBigDataFinal.pptx
BigDataFinal.pptxPentaTech
 
BIGDATAPrepared ByMuhammad Abrar UddinIntrodu.docx
BIGDATAPrepared ByMuhammad Abrar UddinIntrodu.docxBIGDATAPrepared ByMuhammad Abrar UddinIntrodu.docx
BIGDATAPrepared ByMuhammad Abrar UddinIntrodu.docxtangyechloe
 
ppt final.pptx
ppt final.pptxppt final.pptx
ppt final.pptxkalai75
 
IRJET- Scope of Big Data Analytics in Industrial Domain
IRJET- Scope of Big Data Analytics in Industrial DomainIRJET- Scope of Big Data Analytics in Industrial Domain
IRJET- Scope of Big Data Analytics in Industrial DomainIRJET Journal
 
Big Data By Vijay Bhaskar Semwal
Big Data By Vijay Bhaskar SemwalBig Data By Vijay Bhaskar Semwal
Big Data By Vijay Bhaskar SemwalIIIT Allahabad
 

Similar to Big data Ppt (20)

bigdata.pptx
bigdata.pptxbigdata.pptx
bigdata.pptx
 
Big data Analytics
Big data Analytics Big data Analytics
Big data Analytics
 
big-data-8722-m8RQ3h1.pptx
big-data-8722-m8RQ3h1.pptxbig-data-8722-m8RQ3h1.pptx
big-data-8722-m8RQ3h1.pptx
 
big data.pptx
big data.pptxbig data.pptx
big data.pptx
 
Kartikey tripathi
Kartikey tripathiKartikey tripathi
Kartikey tripathi
 
Bigdata " new level"
Bigdata " new level"Bigdata " new level"
Bigdata " new level"
 
big data
big databig data
big data
 
Big data
Big dataBig data
Big data
 
BIG DATA & DATA ANALYTICS
BIG  DATA & DATA  ANALYTICSBIG  DATA & DATA  ANALYTICS
BIG DATA & DATA ANALYTICS
 
Our big data
Our big dataOur big data
Our big data
 
Analysis on big data concepts and applications
Analysis on big data concepts and applicationsAnalysis on big data concepts and applications
Analysis on big data concepts and applications
 
Big data seminor
Big data seminorBig data seminor
Big data seminor
 
Big data and analytics
Big data and analyticsBig data and analytics
Big data and analytics
 
BigDataFinal.pptx
BigDataFinal.pptxBigDataFinal.pptx
BigDataFinal.pptx
 
BIGDATAPrepared ByMuhammad Abrar UddinIntrodu.docx
BIGDATAPrepared ByMuhammad Abrar UddinIntrodu.docxBIGDATAPrepared ByMuhammad Abrar UddinIntrodu.docx
BIGDATAPrepared ByMuhammad Abrar UddinIntrodu.docx
 
Big data-ppt-
Big data-ppt-Big data-ppt-
Big data-ppt-
 
Big data
Big dataBig data
Big data
 
ppt final.pptx
ppt final.pptxppt final.pptx
ppt final.pptx
 
IRJET- Scope of Big Data Analytics in Industrial Domain
IRJET- Scope of Big Data Analytics in Industrial DomainIRJET- Scope of Big Data Analytics in Industrial Domain
IRJET- Scope of Big Data Analytics in Industrial Domain
 
Big Data By Vijay Bhaskar Semwal
Big Data By Vijay Bhaskar SemwalBig Data By Vijay Bhaskar Semwal
Big Data By Vijay Bhaskar Semwal
 

Recently uploaded

Scanning the Internet for External Cloud Exposures via SSL Certs
Scanning the Internet for External Cloud Exposures via SSL CertsScanning the Internet for External Cloud Exposures via SSL Certs
Scanning the Internet for External Cloud Exposures via SSL CertsRizwan Syed
 
My Hashitalk Indonesia April 2024 Presentation
My Hashitalk Indonesia April 2024 PresentationMy Hashitalk Indonesia April 2024 Presentation
My Hashitalk Indonesia April 2024 PresentationRidwan Fadjar
 
Connect Wave/ connectwave Pitch Deck Presentation
Connect Wave/ connectwave Pitch Deck PresentationConnect Wave/ connectwave Pitch Deck Presentation
Connect Wave/ connectwave Pitch Deck PresentationSlibray Presentation
 
"Federated learning: out of reach no matter how close",Oleksandr Lapshyn
"Federated learning: out of reach no matter how close",Oleksandr Lapshyn"Federated learning: out of reach no matter how close",Oleksandr Lapshyn
"Federated learning: out of reach no matter how close",Oleksandr LapshynFwdays
 
Tech-Forward - Achieving Business Readiness For Copilot in Microsoft 365
Tech-Forward - Achieving Business Readiness For Copilot in Microsoft 365Tech-Forward - Achieving Business Readiness For Copilot in Microsoft 365
Tech-Forward - Achieving Business Readiness For Copilot in Microsoft 3652toLead Limited
 
Designing IA for AI - Information Architecture Conference 2024
Designing IA for AI - Information Architecture Conference 2024Designing IA for AI - Information Architecture Conference 2024
Designing IA for AI - Information Architecture Conference 2024Enterprise Knowledge
 
Beyond Boundaries: Leveraging No-Code Solutions for Industry Innovation
Beyond Boundaries: Leveraging No-Code Solutions for Industry InnovationBeyond Boundaries: Leveraging No-Code Solutions for Industry Innovation
Beyond Boundaries: Leveraging No-Code Solutions for Industry InnovationSafe Software
 
Advanced Test Driven-Development @ php[tek] 2024
Advanced Test Driven-Development @ php[tek] 2024Advanced Test Driven-Development @ php[tek] 2024
Advanced Test Driven-Development @ php[tek] 2024Scott Keck-Warren
 
Are Multi-Cloud and Serverless Good or Bad?
Are Multi-Cloud and Serverless Good or Bad?Are Multi-Cloud and Serverless Good or Bad?
Are Multi-Cloud and Serverless Good or Bad?Mattias Andersson
 
"Debugging python applications inside k8s environment", Andrii Soldatenko
"Debugging python applications inside k8s environment", Andrii Soldatenko"Debugging python applications inside k8s environment", Andrii Soldatenko
"Debugging python applications inside k8s environment", Andrii SoldatenkoFwdays
 
costume and set research powerpoint presentation
costume and set research powerpoint presentationcostume and set research powerpoint presentation
costume and set research powerpoint presentationphoebematthew05
 
CloudStudio User manual (basic edition):
CloudStudio User manual (basic edition):CloudStudio User manual (basic edition):
CloudStudio User manual (basic edition):comworks
 
AI as an Interface for Commercial Buildings
AI as an Interface for Commercial BuildingsAI as an Interface for Commercial Buildings
AI as an Interface for Commercial BuildingsMemoori
 
APIForce Zurich 5 April Automation LPDG
APIForce Zurich 5 April  Automation LPDGAPIForce Zurich 5 April  Automation LPDG
APIForce Zurich 5 April Automation LPDGMarianaLemus7
 
SAP Build Work Zone - Overview L2-L3.pptx
SAP Build Work Zone - Overview L2-L3.pptxSAP Build Work Zone - Overview L2-L3.pptx
SAP Build Work Zone - Overview L2-L3.pptxNavinnSomaal
 
Install Stable Diffusion in windows machine
Install Stable Diffusion in windows machineInstall Stable Diffusion in windows machine
Install Stable Diffusion in windows machinePadma Pradeep
 
WordPress Websites for Engineers: Elevate Your Brand
WordPress Websites for Engineers: Elevate Your BrandWordPress Websites for Engineers: Elevate Your Brand
WordPress Websites for Engineers: Elevate Your Brandgvaughan
 
Dev Dives: Streamline document processing with UiPath Studio Web
Dev Dives: Streamline document processing with UiPath Studio WebDev Dives: Streamline document processing with UiPath Studio Web
Dev Dives: Streamline document processing with UiPath Studio WebUiPathCommunity
 
Transcript: New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024
Transcript: New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024Transcript: New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024
Transcript: New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024BookNet Canada
 
SIP trunking in Janus @ Kamailio World 2024
SIP trunking in Janus @ Kamailio World 2024SIP trunking in Janus @ Kamailio World 2024
SIP trunking in Janus @ Kamailio World 2024Lorenzo Miniero
 

Recently uploaded (20)

Scanning the Internet for External Cloud Exposures via SSL Certs
Scanning the Internet for External Cloud Exposures via SSL CertsScanning the Internet for External Cloud Exposures via SSL Certs
Scanning the Internet for External Cloud Exposures via SSL Certs
 
My Hashitalk Indonesia April 2024 Presentation
My Hashitalk Indonesia April 2024 PresentationMy Hashitalk Indonesia April 2024 Presentation
My Hashitalk Indonesia April 2024 Presentation
 
Connect Wave/ connectwave Pitch Deck Presentation
Connect Wave/ connectwave Pitch Deck PresentationConnect Wave/ connectwave Pitch Deck Presentation
Connect Wave/ connectwave Pitch Deck Presentation
 
"Federated learning: out of reach no matter how close",Oleksandr Lapshyn
"Federated learning: out of reach no matter how close",Oleksandr Lapshyn"Federated learning: out of reach no matter how close",Oleksandr Lapshyn
"Federated learning: out of reach no matter how close",Oleksandr Lapshyn
 
Tech-Forward - Achieving Business Readiness For Copilot in Microsoft 365
Tech-Forward - Achieving Business Readiness For Copilot in Microsoft 365Tech-Forward - Achieving Business Readiness For Copilot in Microsoft 365
Tech-Forward - Achieving Business Readiness For Copilot in Microsoft 365
 
Designing IA for AI - Information Architecture Conference 2024
Designing IA for AI - Information Architecture Conference 2024Designing IA for AI - Information Architecture Conference 2024
Designing IA for AI - Information Architecture Conference 2024
 
Beyond Boundaries: Leveraging No-Code Solutions for Industry Innovation
Beyond Boundaries: Leveraging No-Code Solutions for Industry InnovationBeyond Boundaries: Leveraging No-Code Solutions for Industry Innovation
Beyond Boundaries: Leveraging No-Code Solutions for Industry Innovation
 
Advanced Test Driven-Development @ php[tek] 2024
Advanced Test Driven-Development @ php[tek] 2024Advanced Test Driven-Development @ php[tek] 2024
Advanced Test Driven-Development @ php[tek] 2024
 
Are Multi-Cloud and Serverless Good or Bad?
Are Multi-Cloud and Serverless Good or Bad?Are Multi-Cloud and Serverless Good or Bad?
Are Multi-Cloud and Serverless Good or Bad?
 
"Debugging python applications inside k8s environment", Andrii Soldatenko
"Debugging python applications inside k8s environment", Andrii Soldatenko"Debugging python applications inside k8s environment", Andrii Soldatenko
"Debugging python applications inside k8s environment", Andrii Soldatenko
 
costume and set research powerpoint presentation
costume and set research powerpoint presentationcostume and set research powerpoint presentation
costume and set research powerpoint presentation
 
CloudStudio User manual (basic edition):
CloudStudio User manual (basic edition):CloudStudio User manual (basic edition):
CloudStudio User manual (basic edition):
 
AI as an Interface for Commercial Buildings
AI as an Interface for Commercial BuildingsAI as an Interface for Commercial Buildings
AI as an Interface for Commercial Buildings
 
APIForce Zurich 5 April Automation LPDG
APIForce Zurich 5 April  Automation LPDGAPIForce Zurich 5 April  Automation LPDG
APIForce Zurich 5 April Automation LPDG
 
SAP Build Work Zone - Overview L2-L3.pptx
SAP Build Work Zone - Overview L2-L3.pptxSAP Build Work Zone - Overview L2-L3.pptx
SAP Build Work Zone - Overview L2-L3.pptx
 
Install Stable Diffusion in windows machine
Install Stable Diffusion in windows machineInstall Stable Diffusion in windows machine
Install Stable Diffusion in windows machine
 
WordPress Websites for Engineers: Elevate Your Brand
WordPress Websites for Engineers: Elevate Your BrandWordPress Websites for Engineers: Elevate Your Brand
WordPress Websites for Engineers: Elevate Your Brand
 
Dev Dives: Streamline document processing with UiPath Studio Web
Dev Dives: Streamline document processing with UiPath Studio WebDev Dives: Streamline document processing with UiPath Studio Web
Dev Dives: Streamline document processing with UiPath Studio Web
 
Transcript: New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024
Transcript: New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024Transcript: New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024
Transcript: New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024
 
SIP trunking in Janus @ Kamailio World 2024
SIP trunking in Janus @ Kamailio World 2024SIP trunking in Janus @ Kamailio World 2024
SIP trunking in Janus @ Kamailio World 2024
 

Big data Ppt

  • 2. CONTENTS  Introduction  The Need for Big data  Characteristics of Big Data  Volume  Velocity  Variety  Sources of Big Data  Processing Big Data  Big Data Analytics  Benefits of Big Data  Drawbacks of Big Data  Impacts of Big Data on IT  Facts  Future of Big Data  India-Big Data
  • 3. INTRODUCTION  Big Data is high-volume, high-velocity and/or high-variety information assets that demand cost-effective, innovative forms of information processing that enable enhancedinsight, decision making, and process automation  But having data bigger it requires different approaches:  Techniques, tools and architecture  An aim to solve new problems or old problems in a better way  Big Data generates value from the storage and processing of very large quantities of digital information that cannot be analyzed with traditional computing techniques.  Like many new information technologies, big data can bring about dramatic cost reductions, substantial improvements in the time required to perform a computing task, or new product and service offerings.
  • 4. THE NEED FOR BIG DATA • Growth of Big Data is needed – Increase of storage capacities – Increase of processing power – Availability of data(different data types) – Every day we create 2.5 quintrillion bytes of data; 90% of the data in the world today has been created in the last two years alone
  • 5. THREE CHARACTERISTICS OF BIG DATA 3VS Volume • Data quantity Velocity • Data Speed Variety • Data Types
  • 6. 1ST CHARACTER OF BIG DATA VOLUME •A typical PC might have had 10 gigabytes of storage in 2000. •Today, Facebook ingests 500 terabytes of new data every day. •Boeing 737 will generate 240 terabytes of flight data during a single flight across the US. • The smart phones, the data they create and consume; sensors embedded into everyday objects will soon result in billions of new, constantly-updated data feeds containing environmental, location, and other information, including video.
  • 7. 2ND CHARACTER OF BIG DATA VELOCITY  Clickstreams and ad impressions capture user behavior at millions of events per second  High-frequency stock trading algorithms reflect market changes within microseconds  Machine to machine processes exchange data between billions of devices  On-line gaming systems support millions of concurrent users, each producing multiple inputs per second.
  • 8. 3RD CHARACTER OF BIG DATA VARIETY  Big Data isn't just numbers, dates, and strings. Big Data is also geospatial data, 3D data, audio and video, and unstructured text, including log files and social media.  Big Data analysis includes different types of data
  • 9. SOURCES OF BIG DATA  Administrative Data  Transactions  Public Data  Sensor Data  Social media
  • 10. PROCESSING BIG DATA  Integrating disparate data stores  Mapping data to the programming framework  Connecting and extracting data from storage  Transforming data for processing  Subdividing data in preparation for Hadoop MapReduce  Employing Hadoop MapReduce  Creating the components of Hadoop MapReduce jobs  Distributing data processing across server farms  Executing Hadoop MapReduce jobs  Monitoring the progress of job flows
  • 11. BIG DATA ANALYTICS  Examining large amount of data  Appropriate information  Identification of hidden patterns, unknown correlations  Competitive advantage  Better business decisions: strategic and operational  Effective marketing, customer satisfaction, increased revenue
  • 12. BENEFITS OF BIG DATA  Real-time big data isn’t just a process for storing petabytes or exabytes of data in a data warehouse, It’s about the ability to make better decisions and take meaningful actions at the right time.  Our newest research finds that organizations are using big data to target customer-centric outcomes, tap into internal data and build a better information ecosystem.  Big Data is already an important part of the $64 billion database and data analytics market
  • 13. DRAWBACKS OF BIG DATA  Security and Privacy issues  Performance  Data Representation 13
  • 14. IMPACTS OF BIG DATA ON IT  Big data is a troublesome force presenting opportunities with challenges to IT organizations.  By 2015 4.4 million IT jobs in Big Data ; 1.9 million is in US itself  India will require a minimum of 1 lakh data scientists in the next couple of years in addition to data analysts and data managers to support the Big Data space.
  • 15. FACTS  FB generates 10TB daily  Twitter generates 7TB of data Daily  IBM claims 90% of today’s stored data was generated in just the last two years.  Decoding the human genome originally took 10years to process; now it can be achieved in one week.
  • 16. FUTURE OF BIG DATA  $15 billion on software firms only specializing in data management and analytics.  This industry on its own is worth more than $100 billion and growing at almost 10% a year which is roughly twice as fast as the software business as a whole.
  • 17. INDIA – BIG DATA  Big data analysis helped in parts, responsible for the BJP and its allies to win Indian General Election 2014.  The Indian Government utilises numerous techniques to ascertain how the Indian electorate is responding to government action, as well as ideas for policy augmentation

Editor's Notes

  1. Acco.to IBM