Overview of Bigdata Analytics

3. Big Data
So large data that it
becomes difficult to
process using the
traditional system

4. Characteristics of Big Data
Velocit
y
• Data
Speed
Volume
• Data
quantity
Variety
•Data
Types

5.  Volume refers to huge amount of data
being generated every minute.
 90% of the data we have now is
created in just past 2 years.
 Cisco estimates internet traffic
4.8ZB per year.
 3 billion people would be online by
2015 .
Volume

6.  Velocity refers to SPEED at which
new data is being generated and moves
around.
 It includes Real time working
systems such as Online banking.
 Need of low response time.
Velocity

7.  Variety refers to various
datatypes which we can now use.
 Earlier focus was on neat and
structured data kept in form of
tables in RDBMS.
 80% of data available now is
unstructured data
 Data in the from of text,
videos, audios and pictures.
Variety

8. Mobile Devices
Social Media
E-Commerce
E-Mails

10. Where does data come from?

11. What good is all of this data?
Wisdom

12. Why Big Data
– Increase of storage capacities
– Increase of processing power
– Availability of data
– 90% of the data in the world today has been
created in the last two years alone

13. Big Data Analytics
• Examining large amount of data
• Appropriate information
• Competitive advantage
• Better business decisions
• Effective marketing, customer satisfaction, increased
revenue

14. Applications for Big Data Analytics
Multi-channel sales
Smarter Healthcare Finance
Log Analysis Traffic Control
Search Quality
Manufacturing Trading Analytics
Telecom

15. NoSQL : non-relational or at least non-SQL database
solutions such as HBase (also a part of the Hadoop
ecosystem), Cassandra, MongoDB, Riak, CouchDB, and
many others.
Hadoop: It is an ecosystem of software packages,
including MapReduce, HDFS, and a whole host of other
software packages

16. What is Hadoop?
 Hadoop is a open source framework
 Java-based programming framework
 Processing and storing of large data
sets
 Distributed computing environment.

17. References
•http://searchbusinessanalytics.techtarget.com/
Experts sound off on big data , Analytics and its tools
• http://www.ibmbigdatahub.com/infographic/four-vs-big-
data
Big data and analytics hub
• https://bigdatauniversity.com/bdu-wp/bdu-course/
hadoop-fundamentals-i-version-3/
Hadoop fundamentals