Big data comes from various sources in different formats and structures. It includes social media data, search engine data, medical records, and IoT device data. YouTube alone generates billions of views from over 1 billion users uploading 1.2 million videos daily. Big data is characterized by its variety, velocity, and volume. Hadoop is an open source framework used to process and store big data. It has two core components - HDFS for storage and MapReduce for processing. Hadoop distributes data and tasks across nodes, provides fault tolerance, and scales dynamically with hardware.

1. Big Data Analysis
MOHAMMAD ALFAWAREH

2. What is the Big data
Big data: are massive and complex amount of data
that generated from different sources, with different
format structure, unstructured and semistrucured .

3. Resources of Big data
Social Sites Data :- such as Instagram , my space, snapchat Facebook, whatsup
All of these S.M generate photos, text, videos and emotions'
Search Engine Data: millions of peoples make searches in seconds and search engines deal with
serval type of data bases.
Medical History Data: hospital and clinks produce millions of transactions to the paints
regards history or from researches on some diseases .
IOT devices: with this revolutions billions of devices will generate the data in difference format.
Online shopping:-

4. YouTube Statistics
Every day people
watch hundreds of
millions of hours
over a billion users
people across the
world are
uploading 1.2
million videos
generate billions of
views
over 100 hours per
minute and this
number is ever
increasing

5. Characterize of B.D
Varity
Vilocity
Volume

6. Why now Big data analysis
1. Low cost storage to store data that was discarded earlier
2. Powerful multi-core processors
3. Low latency possible by distributed computing: Compute
clusters and grids connected via high-speed networks
4. Virtualization Partition, Aggregate, isolate resources in any
size and dynamically change it Minimize latency for any
scale
5. Affordable storage and computing with minimal man power
via clouds
6 Possible because of advances in Networking

7. Why we need Big data analysis
Businesses
intelligence
Make Our
life Easy
Military
App
Decrease
Average of
Diseases

8. Old method to solve the data base issues
RDMS was used to store the data in single space
when the client send a job the device will process the data and send it back to the client
,unfortunately with rapid generation of the data in huge volume every day like exa,peta,zeta
and in different format this method become ineffective for couple of reasons
Total data production is increasing day by day in a very large amount
We need huge storage devices and management system to this data
We need to increase the processing unit scale in due to some specific app need real time
processing.
Increase Colling and power consumptions .

9. What is Hadoop
Hadoop: is open source frame work used to
process and storage big data ,used in big
companies like google , Facebook, twitter.

10. Hadoop components
The Hadoop has two core components
one to the storage called HDFS the ides come from GFS.
And the another to the processing called Map-reduce.

11. HDFS

12. Map-Reduce

13. Hadoop Advantage
It is compatible on all the platforms.
 It distributes the data and tasks across the nodes automatically, which allows the users to
write and execute the distributed systems quickly.
 The library has the API to detect and handle failures at the application layer which relieves the
framework to rely on the hardware for fault tolerance.
The framework continues to operate smoothly with the addition and removal of servers
dynamically.