This document discusses big data, providing definitions and outlining its key characteristics of volume, velocity, and variety. It describes processes involved like integrating disparate data stores and employing Hadoop MapReduce. Sources of big data are identified as mobile devices, sensors, social media, etc. Tools used include distributed servers, storage, and databases. Statistics on data generated by companies like Facebook and Twitter are provided. Applications of big data include improving science, healthcare, finance, and security. Advantages include access to vast information, while disadvantages include costs and privacy issues.

1. BIG DATA
Done by,
B.SENTHIL PANDI(17MC040)
II YEAR MECHATRONICS
SNS COLLEGE OF TECHNOLOGY

2. OUTLINE :
• INTRODUCTION
• CHARACTERISTIC OF BIG DATA
• PROCESSES IN BIG DATA
• BIG DATA SOURCES
• TYPES OF TOOLS
• BIG DATA STATISTICS
• APPLICATIONS OF BIG DATA
• ADVANTAGES AND DISADVANTAGES
• CONCLUSION

3. INTRODUCTION :
• Big data refers to data sets that are too large or complex
for traditional data-processing application software to
adequately deal with.
• Firms like Google, eBay, LinkedIn and Facebook were
built around big data from the beginning.
• Big data generates value from storage and process very
large quantities of digital information that cannot be
analyzed with traditional computer system.

4. CHARACTERISTICS OF BIG DATA :

5. VOLUME :
• A typical PC might have 10gb of storage in 2000.
• Today, Facebook ingests 500 terabytes of new
data everyday.
• Boeing 737 will generate 240 terabytes of flight
data during a single flight across US.
• Thus the big data source must be very vast in
volume.

6. VELOCITY :
• Clickstreams and ad impressions capture user behaviour at
millions of events per second.
• Machine to machine processes exchange data between
billion of devices.
• Infrastructure and sensors generate massive log data in real
time.
• Online gaming systems supports millions of concurrent
users, each producing multiple inputs per second.

7. VARIETY :
• Big data is not just numbers but also collection of
3D data, audio and video, unstructured text,
including log files and social media.
• Traditional database systems are designed only to
store small amount of information.
• Big data analysis includes different types of data.

8. PROCESSES IN BIG DATA :
I. INTEGRATING DISPARATE DATA STORES :
• Mapping data to programming frame network.
• Connecting and extracting data from storage.
• Transforming data for processing.
• Subdividing data in preparation for Hadoop MapReduce.
II.EMPLOYING HADOOP MAPREDUCE :
• Creating the components of Hadoop MapReduce jobs.
• Distributing data processing across server farms.
• Executing Hadoop MapReducing jobs.
• Monitoring the progress of job flows.

9. BIG DATA SOURCES :

10. DATA GENERATION POINTS :
• Mobile devices
• Microphones
• Readers/Scanners
• Science facilities
• Programs/Software
• Social media
• Cameras

11. TYPES OF TOOLS :
 Where processing data is hosted?
Distributed servers/cloud(eg. Amazon EC2).
 Where data is stored?
Distributed storage(eg. Amazon S3).
 How data is stored and indexed?
High performance schema-free databases(eg. MongoDB).
 What operations are performed on data?
Analytic/Semantic processing.

12. BIG DATA STATISTICS :
• Facebook generates 10TB of data daily.
• Twitter generates 7TB of data daily.
• IBM claims 90% of today’s stored data is
generated in the last two years.
• Everyday we create 2.5 quintillion bytes of data.
• Walmart handles more than 1 million customer
transactions every hour.

13. APPLICATIONS OF BIG DATA :

14. ADVANTAGES OF BIG DATA :
• It helps in improving science and research. It improves
healthcare and public health with availability of record of
patients.
• It helps in financial tradings, sports, polling, security/law
enforcement etc.
• Any one can access vast information via surveys and
deliver answer of any query.
• Every second additions are made.
• One platform carry unlimited information.

15. DISADVANTAGES OF BIG DATA :
➨Traditional storage can cost lot of money to store
big data.
➨Lots of big data is unstructured.
➨Big data analysis violates principles of privacy.
➨Big data analysis results are misleading
sometimes.
➨Speedy updates in big data can mismatch real
figures.

16. CONCLUSION :
• Big data brings new and existing
opportunities to companies who utilize the
platforms available.
• In this information Era, big data technology
has got its own importance for businesses.
• It has got lot of opportunities in the
upcoming days.

17. THANK YOU