Big data presenation
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The document discusses big data concepts including volume, velocity, variety and value of data. It covers challenges in big data such as handling different data types, scalability, and privacy issues. It also discusses tools and techniques for big data analytics including Hadoop, MapReduce, and integrating R and Hadoop for more accurate analytics and increased performance.
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- 3. •Volume •Velocity •Veracity •Variety •Value
- 4. •MEGA BYTE •GIGA BYTE •TERA BYTE •PETA BYTE •EXTRA BYTE •ZETTA BYTE
- 5. •Collect •Discover •Process •Manage •Generate
- 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
- 8. •Variety of Formats •Ambiguity of Data •Abstracted layer of Hierarchy •Lack of Meta Data
- 9. •Finding patterns • Deriving meaning • Making decisions • Responding to the world with intelligence
- 10. •Lexical Analysis •Syntactic Analysis •Semantic Analysis •Sentimental Analysis
- 11. •Big Table •Business Intelligence •Cassandra •Hadoop and MapReduce •R
- 12. •Deals with extracting information from data •Use this information to predict outcomes •Find patterns that predict similar outcome in future
- 13. •Hadoop and Mapreduce •Integrating R and Hadoop •Tools like RHIPE and RHadoop
- 14. By combining capability of Hadoop and R by using Rhadoop tool the performance and accuracy of data analytics can be increased
- 15. THANKS
- 16. Queries ?