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Big data
- 6. •How to handle Heterogeneity
•Scalability (volume)
•Structured / Semi structured/
Unstructured data handling
•Timeliness response
•Handle privacy and security issues
- 7. •Development of analytics
•Design & develop appropriate data
models
•Developments of tools
•Creating Data warehouse & Mining
techniques
•Business intelligence
•Storage consideration
- 12. •Deals with extracting information
from data
•Use this information to predict
outcomes
•Find patterns that predict similar
outcome in future
- 14. By combining capability of Hadoop
and R by using Rhadoop tool the
performance and accuracy of data
analytics can be increased