Big Data Hadoop, differences and real time applications ppt – IQ Online Training

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Big Data Hadoop

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What is Hadoop?
Hadoop which is formerly known as Apache Hadoop
is a completely open source distributed framework
which manages huge amounts of data processing and
storage for the big data applications which run
in clustered systems. Hadoop handles structured
and unstructured data giving more flexibility for
the users than relational databases and data
warehouses in collecting and analyzing data.
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What is Big Data?
Big Data is a term coined to describe enormous or
huge chunks of both structured and unstructured
data which even traditional data-processing
applications cannot handle efficiently. In many
businesses, Big Data can be used to analyze the
insights of the data that would eventually help
in making better decisions and strategic business
moves.
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Difference between Big Data and Hadoop
As said BIG DATA is a collection of huge
volumes of data. Since, it cannot be processed by
traditional methods because most part of it is
unstructured Hadoop has evolved as a solution to
this problem. Big Data and Hadoop are not
comparable, since one has a problem and other
evolved as a solution.
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Some Real-time Industry Applications of Hadoop

• Improving business performance by analyzing
  customer data in real time.
• Used in social media to manage posts, images,
  videos, and content
• Managing traffic on roads.
• Archiving Emails.
• Hadoop Computing Cluster is used to Process Rat
  Brain Neuronal Signals.
• Fraud detection.
• Used in some Public sector fields such as
  intelligence, defense, cyber security and
  scientific research.
• In the Financial industries to identify fraud
  patterns, reduce risk, precisely target market
  campaigns, customer satisfaction etc.
• Many Advertisements Targeting Platforms are
  using Hadoop in ways such as identify and analyze
  clickstream, video and social media data.

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