A process in which big data( bulk of data) is examined to uncover hidden patterns and other useful business information. Generally, this is done with the help of big data analytics tools that support both predictive and prescriptive analytics applications running on the data.

1. Hadoop – A
Big Data TOOLKIT

2. What does big data analytics mean?
• A process in which big data( bulk of data) is examined to uncover hidden patterns
and other useful business information.
• Generally, this is done with the help of big data analytics tools that support both
predictive and prescriptive analytics applications running on the data.

3. Who uses big data analytics tools?
Data Scientists
Business
Analysts
Business Managers
IT
Developers

4. What’s Hadoop in data analytics?
• Hadoop is an open source framework for data storage and running clusters of
application.
• It provides storage of any kind of massive data with massive processing powers
and has the capability of handling limitless tasks.

5. Why Hadoop?
Capacity to store and process huge amount of any sort of
information rapidly makes Hadoop an important tool. With data
volumes and assortments continually expanding, particularly
from social media and online networking, Hadoop makes it
easier to manage all sorts of data.

6. Features
• Computing Power.
Hadoop features distributed model of computing big data which in turn
makes Hadoop a reliable data storage medium. The more computing nodes
you use the more processing power you have.
• Fault tolerance.
Data and application handling are ensured against hardware failure. If any of
the data hubs goes down, work is automatically redirected to other data
nodes to make sure the distributed computing does not fail. Various
duplicates of all information are put away consequently.
• Flexibility.
Hadoop allows you to store as much data as you want to and decide how you
want to use it later. Unlike other databases, you don’t have to preprocess data
before storing it. That includes unstructured data like text, images, and
videos.

7. Other Features
• Low cost.
The Hadoop open-source framework is free and uses
commodity hardware to store large quantities of data.
• Scalability.
Grow your system easily by adding nodes to it for more data
handling. The little administration is required.

8. Thank You!!