BIG DATA SUMMARY
It is all
their data.
Big Data is a
synthesis of or compendium of many technologies.
It is very
useful to learners who have a few years of experience.
Big Data – In built
To name a few
1. Many applications
2. A lot of space
3. Many strategies
4. Many wonder tools
5. Many technologies
6. Many talent needs
7. Many Operating Systems etc.
It is
multidimensional in one.
It is handled
by Tensor based computation.
Big Data – Technologies
1] Hadoop
It is the
ecosystem of Big Data.
2] HDF
3] MapReducer
It is a
machine instruction set.
4] PIG
It is a high
level language.
5] HIVE
It is a high
level language.
6] Jaql
It is a high
level language.
7] WibiData
8] PLATFORA
9] FLUME
10] Zookeeper
Big Data – Applications
If we know the
various applications, really we love it.
1. Internet documents
2. Astronomy
3. Atmosphere
4. Genomics
5. Biogeochemical
6. Biological
7. Military surveillance
8. Medical records
9. Photography
10. Video
11. e-commerce
12. sensor networks
13. Spot business trends
14. Quality
of research
15. Prevent diseases
16. Legal citations
17. Combat crime
18. Road traffic
19. Cameras
20. Identification
21. Wireless sensor networks
Etc.,
Big Data – Space
Space is
provided by EMC [Isilon One FS OS]
1. Skytree
2. BigData in cloud
2.5 quintillions
[ 10 18 bytes ] space is created every day.
\Big
Data – Technologies
1. Business
intelligence
2. Cluster
analysis
3. Data
mining
4. Predictive
modelling
5. SQL
6. A/B
testing
7. Crow
Sourcing
8. Textual
analysis
9. Sentiment
analysis
10. Network
analysis
Big Data
– Operating Systems
1] Cloudera
Cloudera’s Technology breaks data into chunks
2] Hadoop
It is the ecosystem of Big Data.
This contains
1. Resource
Manager
2. Kernel
3. Filesyst4em
3] YARN
Yet Another Resource Negotiator.
It made impossible, possible.
It made Hadoop into multi-application OS.
4] EMC
Isilon OneFS OS.
Speed,
Scalability
Security
Protection
It updates Big Data storage.
5] a’ La
Windows
It examines files.
Big Data
- vendor tools
1. leading
business intelligence
2. Microsoft
SQL
3. SAP
business objects
4. Oracle
business intelligence
5. IBM
congnoss
6. SAS
7. Microstrategy
8. Qlik
tech
9. Tibco
spot fire
10. Platfora
Big Data
– Strategies
1. Performance
Management
2. Data
exploration
3. Social
analytics
4. Decision
science
Big Data
– Talent needs / Potentiality
1. Evaluate
the internal talent pool
2. Filling
your talent gap from sources
3. Cross
training
4. Empower
your team
Big Data
- iOS settings
iPod
iPad
iphone
iOS
apps
data
Memory
storage
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