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Big Data
Analysis
Who Am
I?
 Digital Marketing ~ WordPress ~ Web
Marketing ~ Virtual Assistant
 https://twitter.com/marufcsediu
 https://www.facebook.com/RionMaruf
 https://www.linkedin.com/in/marufcsediu/
 Key Skills: Digital Marketing, Virtual
Assistant, CRM, WordPress, Email Marketing,
Lead Generation, Internet Research, HTML5,
Big Data Analysis
What is
Big Data?
Big data is a term that explains the large volume
of data (both structured and unstructured). Big
data can be analyzed for insights that show the
way to better decisions and strategic business
moves.
While the term “big data” is fairly new, the act of
gathering and storing bulky amounts of
information for ultimate analysis is ages old. Big
Data concept gained momentum in the early
2000s.
3 V’s of Big Data
“
Volume: In Big Data, Volume refers to the vast
amount of data generated every second.
Velocity: In Big Data, Velocity refers to the speed at
which new data is generated and also the speed at
which data moves around
Variety: It refers to the different types of data we can
use. For example: text, audio/sound, video etc..
Some Big
Data
Source
 Social Networking Profiles
 Activity Generated Data
 SaaS and Cloud Apps
 Public Web Information
 NoSQL Database
 MapReduce results
 Data Warehouse appliances
 Legacy Documents etc..
Structured Data
Structured data refers
to kinds of data with a
high level of
organization, such as
information in a
relational database.
Structured vs
Unstructured
Data
Unstructured Data
Unstructured data refers to
information that either
does not have a pre-defined
data model or is not
organized in a pre-defined
manner.
What is Big Data?
What is
HADOOP?
‘‘Flexible and available architecture for
large scale computation and data
processing on a network of commodity
hardware.’’
It’s a Open Source Software and Hardware
Commodity.
Why
HADOOP
is Used?
 Searching
 Log Precessing
 Recommendation System
 Analytics
 Image and Video Analysis
 Data Retention
What is Big Data?
High Level
Hadoop
Architecture
High Level
Hadoop
Architecture
Thank You

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What is Big Data?

  • 2. Who Am I?  Digital Marketing ~ WordPress ~ Web Marketing ~ Virtual Assistant  https://twitter.com/marufcsediu  https://www.facebook.com/RionMaruf  https://www.linkedin.com/in/marufcsediu/  Key Skills: Digital Marketing, Virtual Assistant, CRM, WordPress, Email Marketing, Lead Generation, Internet Research, HTML5, Big Data Analysis
  • 3. What is Big Data? Big data is a term that explains the large volume of data (both structured and unstructured). Big data can be analyzed for insights that show the way to better decisions and strategic business moves. While the term “big data” is fairly new, the act of gathering and storing bulky amounts of information for ultimate analysis is ages old. Big Data concept gained momentum in the early 2000s.
  • 4. 3 V’s of Big Data
  • 5. “ Volume: In Big Data, Volume refers to the vast amount of data generated every second. Velocity: In Big Data, Velocity refers to the speed at which new data is generated and also the speed at which data moves around Variety: It refers to the different types of data we can use. For example: text, audio/sound, video etc..
  • 6. Some Big Data Source  Social Networking Profiles  Activity Generated Data  SaaS and Cloud Apps  Public Web Information  NoSQL Database  MapReduce results  Data Warehouse appliances  Legacy Documents etc..
  • 7. Structured Data Structured data refers to kinds of data with a high level of organization, such as information in a relational database. Structured vs Unstructured Data Unstructured Data Unstructured data refers to information that either does not have a pre-defined data model or is not organized in a pre-defined manner.
  • 9. What is HADOOP? ‘‘Flexible and available architecture for large scale computation and data processing on a network of commodity hardware.’’ It’s a Open Source Software and Hardware Commodity.
  • 10. Why HADOOP is Used?  Searching  Log Precessing  Recommendation System  Analytics  Image and Video Analysis  Data Retention