this presentation will help you to teach someone the basics of big data. it has less information on the slides with for graphical representation. slide 6 - shows how a traditional centralized system fail to process big data slide 16 - data produced and transmitted from sensing devices slide 17 - The Internet of Things is the network of physical devices, vehicles, home appliances, and other items embedded with electronics, software, sensors Smart alarm gets a notification from traffic detection sensors and wake you up early in the morning. “never get late to office due to traffic” slide 26 - The #ShareaCoke campaign began in Australia in 2011 and then moved throughout the world  Targeting “millennials” (people born from 1980–2000) the campaign started with generic terms and 150 of the country’s most popular first names From the hashtags in Instagram and twitter they analyzed that the sales are going high and then even started to customize coke can online for the customers slide 29 - to find new cures and better understand and predict disease patterns.  slide 30 - Lets the sportsman know their ranking and improve accordingly/ learn their mistakes

1. Big Data
Nimansa Athukorala
Team – OTC
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2. Content
1. Introduction to Big Data
2. History
3. Types of Data
4. 3 Vs in Big Data (characteristics of Big data )
5. Uses of Big Data
6. Disadvantages in Big data
7. Recap
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3. Introduction to Big Data
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4. What is Big Data ?
Massive volume of both structured and unstructured data
that is so large, it is difficult to process using
Traditional database and Software techniques
-Wikipedia
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5. 230
Million
Tweets
per
day
294
Billion
Emails
per
day
72 Hours
of video
uploaded
every
minute
100 Tera
bytes
uploaded
every
day
Stats from : www.geekfence.com
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6. Nimansa 6

7. History
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8. 5 Exabyte of data were created from
dawn of time
until 2003
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9. 1 Exabyte = Billion Gigabytes (1e+9)
&
we create 5 exabyte
or more every 2 days
now
Said by - Eric Schmidt (Chairman of Google)
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10. Evolution of Data sources
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11. Types of Data
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12. Types of Data
•Activity Data
•Conversation Data
•Photo and Video image Data
•Sensor Data
•The Internet of things Data
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13. Activity Data
Listening to Music using Spotify
Online shopping and online
money transferring
Reading a eBook using a Kindle
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14. Conversation Data
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15. Photo and Video image Data
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16. Sensor Data
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17. The Internet of things Data
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18. 3 Vs in Big Data
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19. 3 Vs – Characteristics of Big Data
•Volume
•Velocity
•Variety
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20. Volume
•Refers to the vast amounts of data
generated every second.
•Data across the world is which are stored
and analyzed
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21. Velocity
Refers to the speed at which new data is
generated
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22. Source : buzzsumo.com
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23. Variety
Refers to the different types of data we can
now use
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24. Uses of Big Data
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25. Understanding and Targeting
Customers
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26. Understanding and Optimizing Business
Processes
#ShareaCoke
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28. Personal Quantification and
Performance Optimization
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29. Improving Healthcare and Public Health
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30. Improving Sports Performance
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31. Disadvantages of
Big Data
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32. •The analysis extracted through big data can be
deceitful
•Processing massive amounts of data is time
consuming and costly
•Personnel data might be exposed to external parties
Eg - Facebook users' data breach ( 31st March 2018 )
•Some social media users might get uncomfortable
with the advertisements displayed related to search
history
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33. Recap
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34. • Big data is a Massive volume of data that can not be handled using
traditional techniques
• Until 2003 we created 5 Exabyte of data but now we create 5 Exabyte
of data every 2 days
• There are 5 types of data
• Big data has 3 characteristics often refer as 3 Vs
• Big data is widely used for marketing, finance , healthcare and many
more
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35. References
• http://eminenture.weebly.com/blog/5-advantages-and-disadvantages-of-big-
data?utm_campaign=Submission&utm_medium=Community&utm_source=GrowthHackers.com
• http://timesofindia.indiatimes.com/articleshow/63433451.cms?utm_source=contentofinterest&utm_medium=text&utm_campaign=cppst
• https://www.google.lk/search?q=machine+learning+vs+big+data&rlz=1C1CHBD_enLK798LK798&oq=machine+learning+vs+big+data&aqs=chr
ome.0.0j69i60j0l4.10047j1j1&sourceid=chrome&ie=UTF-8
• https://www.ahajournals.org/doi/10.1161/CIR.0000000000000558
• https://www.datapine.com/blog/big-data-examples-in-healthcare/
• https://www.educba.com/big-data-vs-machine-learning/
• https://medium.com/@kwindle/share-a-coke-and-a-word-how-coca-cola-captured-millennials-through-word-of-mouth-marketing-
44896573d21c
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