Big data refers to the enormous amounts of data being collected from people's online activities every day. This data is stored in large data centers that contain shelves of high-capacity storage drives to house people's data from around the world in a temperature-controlled environment. Hadoop and MapReduce are key applications used to analyze this big data. Hadoop uses a master-slave setup to distribute data across nodes for storage, while MapReduce uses mappers to break data into chunks and reducers to process the mapper output and generate new results. Together, these tools help analyze the vast amounts of collected data to provide useful insights.

1. Under the guidance of,
Sir Sourabh Bhattacharya.
Presented by:
Akash Das
Akansha Kumari
Aishik Das
Adriza Bera

2. WHAT ACTUALLY BIG DATA IS…?
Now, on our day to day lives, we do many things after we wake up in the morning, like
As per the records, it is one of the major things highly done by people nowaday
Checking out the social media
Reading NEWS
People with a working background do stay updated with news everyday

3. w, have you ever thought of the suggestions you get, while you’re trying to google somethi

4. Or when you visit a website, these are kind of hoardings which we see on buildings right?
Yeah, it’s the same thing, but in an electronic format, and much advanced manner.
Whatever you’ve been searching quite frequently, would be appearing to you?
Ever noticed that?

5. So what do we get in common?
This thing right in our hand, does much more things we can just think of, just under our noses.

6. Yeah you guessed it quite right, anything you’re surfing on the internet is not just your property, its being collected ever
So if you think your data is being collected, then there are over 100 crore people in India itself.
HOW IS THIS HAPPENING…???
How and where do we store so much of data?
• That’s what Big Data is, and managing the Big Data is a very tough task.
• For storing the data we need storage devices isn’t it?
• How about a storage device to store 100 crore people’s data?
• Imagine the size of Hard Drive you would be requiring!!!

7. The large infrastructure, looks more like a factory, isn’t it?
But it isn’t, it’s the Facebook’s data centre in Denmark.
They store the large Terabytes and Petabytes of people’s data he
Now, what does a data centre contain?
In movies, you might’ve seen, these kind of shelves with blinking lights,
They are actually shelves with high storage capacity drives,
Just like our hard drives, they are used to store the peoples data
from all around the world.
In a highly facilitated place with temperatures to be maintained, so that
they don’t get fused with heat

8. Now, we’re well aware of what a data centre is, but how to manage such enormous amount of data,
So, considering the numerous amount of festivals in a country like India, you might be observing the change in
your feed showing you the best deals and other things related to the festival.
Analysing the data
• How is the data being analysed?
• A very big question in every person’s head.
• Well, there are many people who are trying to build tools with which we can analyse the enormous data.
• Lets have a look at some reknowned applications:

9. Now talking about the first application,
Hadoop: It contains

10. • Basically enormous amount of storage is required to store enormous amount of data.
• So, in here we’ve a master-slave design,
• Master or NameNode: It keeps the track of the different types of changes made where each component is stor
• Slave or DataNode: It stores the data sent by the master and sends back the data when required, as a slave do

11. • From the above NameNode or DataNode, all are basically computers only, which are sharing their hard drive
for distributed storage.
• We also know that there’s a master for the slave, who keeps a track of the activities going on, inside the
slaves, how much space is left, and other stats.
• Now, basically what HDFS master or NameNode does is distributing a certain file in equal sizes and storing
each in different DataNodes or slaves.
• Means it’ll distribute the data into certain parts of equal sizes and store into the DataNodes, hence the name
distributed storage.
• Now, what if the master dies or NameNode stops working, the data would be lost as the data entry registry is
maintained by it, hence, we could suffer a data loss, so to overcome such conditions we’ve a secondary
master or NameNode, which comes into action when the primary master dies.
• Therefore, during making any changes into the filesystem, the changes are noted down and the image of the
updated registry is passed on to the secondary one.

12. • Now, MapReduce helps us in computing the data we got in HDFS, the data might be unsorted or we need to
sort in a particular way.
• Here also, we’ve two parts such as:
• Mapper: The mapper processes the data and creates several small chunks of data.
• Reducer: The Reducer’s job is to process the data that comes from the mapper. After processing, it produces a new
set of output, which will be stored in the HDFS.

13. • Mapper − Mapper maps the input key/value pairs to a set of intermediate key/value pair.
• JobTracker − Schedules jobs and tracks the assign jobs to Task tracker.
• Task Tracker − Tracks the task and reports status to JobTracker.
• During a MapReduce job, Hadoop sends the Map and Reduce tasks to the appropriate servers in the
• Most of the computing takes place on nodes with data on local disks that reduces the network traffic.
• After completion of the given tasks, the cluster collects and reduces the data to form an appropriate result,
and sends it back to the Hadoop server.

14. So till now, we’ve been how the Big Data works and how it is collected and analyzed, but how do Big Data
help us in
real life.
1. Help us predict weather
forecasts.
2. Help us prevent cyberattacks.
3. Help us predict diseases.

15. THANK YOU
For your valuable time
Once we know something, we find it hard to imagine what it was like not
to know it.