This presentation is about basics of Big data Analytics along with Characteristics,Challenges,Structures,Differences between Traditional and Big data,How Big data is getting benefited in Healthcare Industry,Big data in Real time

1. Bhagath Gopinath

2. What is Big data?
Bhagath Gopinath

3.  Process of
 collecting,
 organizing and
 analyzing large sets of data
 Enables an organization to process extremely large
volumes of data.
 Analyze data and draw conclusion to help
organization to drive better business decisions in
the future.
Bhagath Gopinath

4. Challenges in Big data
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5. Big data challenges include
- Capturing data
- Data storage
- Data analysis
- Search
- Sharing
- Transfer
- Visualization
- Querying
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6. - Updating
- Information privacy
- Data Source
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7.  In the past few years, there has been a massive
increase in Big Data start-ups, all trying to deal
with Big Data and helping organizations to
understand Big Data.
 Thereby more and more companies are slowly
adopting and moving towards Big Data
 The large Big Data revolution is still ahead of us so
a lot will change in the coming years.
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8.  This is achieved through integration of traditional
HTML-style web pages with vast back-end
databases built on SQL.
 5.5 million people are already using Facebook, to
upload and share their own data with friends.
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9. Brief History of Big data
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10. Big data Characteristics
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11. Bhagath Gopinath

12. Volume
 This refers to the vast amounts of data generated
every second.
 This can handle data in Zettabytes or Brontobytes.
 Big data tools use distributed systems so that we
can store and analyse data across databases that
are dotted around anywhere in the world.
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13. Velocity
 Refers to the speed at which new data is generated
and the speed at which data moves around.
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14. Variety
 Refers to the different types of data use.
 In the past we only focused on structured data that
neatly fitted into tables or relational databases,
such as financial data.
 In fact, 80% of the world’s data is unstructured
(text, images, video, voice, etc.)
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15. Veracity
 Refers to the messiness or trustworthiness of
the data.
 With many forms of big data quality and accuracy are
less controllable.
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16. Bhagath Gopinath

17. Differences between Normal and
Big data
Sl.
No
Traditional Data Big Data
1. Support only Structured data Supports any formats of data
2. Size of data is very small Size is more than traditional data size
3. This is easy to work or
manipulate
Difficult to handle data
4. Normal system configuration is
sufficient
High system configuration is required
5. Traditional database tools is
enough
Special tools are required
6. Normal functions are sufficient Special kinds of functions are required
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18. Structures of big data
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19. Bhagath Gopinath

20. Bhagath Gopinath

21. Structured Data Example
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22. Semi structured data Example
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23. Bhagath Gopinath

24. Quasi Structured Data Example
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25. Bhagath Gopinath

26. Tools in Big data
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27. Bhagath Gopinath

28. Real time in Big data
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29. Bhagath Gopinath

30. Big data in Healthcare
 Healthcare analytics has a lot of positive and life
saving outcomes.
 It has the potential to reduce costs of treatment, avoid
preventable diseases and improve the quality of life in
general.
 Organizations are getting sufficient data that helps
them understand what the patient needs are.
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31. Why?
 The healthcare industry faces multiple challenges.
 By using Big data,it will be highly efficient
for healthcare sector to
 Capture patient information
 provide treatment for patients based on the disease.
 Handle vast amount of data like financial, clinical, R&D,
administration and operational data
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32. How big data impacts?
 Patient engagement could be enhanced
 Patient health tracking
 Personal injuries
 Cost reduction
 Increased Access To Real-Time Health Stats
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33. Benefits of big data
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34. Advantages
 Through big data, healthcare organizations can create
holistic, personalized, comprehensive patient profiles
and detect diseases at much earlier stages to be treated
more effectively.
 Healthcare organizations can also expect to boost
security, as well, by detecting healthcare fraud more
easily and effectively.
 Mobile health applications such as telehealth and
wearables like, Fit Bit, will also grow and provide
consumers with healthcare services and information
instantly.
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35. Conclusion
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36.  Like other key developments in data storage, data
processing and the Internet, Big Data is just a
further step that will bring change to the way we
run business and society.
 Big data has also played an important role in
Healthcare Industry
 Big data in healthcare deems to have great
potential to steer the industry in a more efficient
and cost-efficient future.
Bhagath Gopinath