1. BIG DATA ANALYTICS
Presented by :
Samik Gupta
Amit Kumar
Siddharth Dixit
Nishant Jain

2. WHAT IS “BIG DATA”?
 Big data is a term applied to data sets that grow so large and
complex that it is beyond the ability of commonly used software
tools to capture, manage, and process the data within a
tolerable elapsed time.
 Characteristics of Big data:
 Volume
 Variety
 Velocity
 Value

3. WHEN TO CONSIDER BIG DATA SOLUTION?
 Big data solutions are ideal for analyzing not only raw
structured data, but semi-structured and unstructured data
from a wide variety of sources
 Big data solutions are ideal when all, or most, of the data
needs to be analyzed versus a sample of the data; or a
sampling of data isn’t nearly as effective as a larger set of
data from which to derive analysis
 Big data solutions are ideal for iterative and exploratory
analysis when business measures on data are not
predetermined

4. WHAT CAN YOU DO WITH BIG DATA?
• Financial Services
o Fraud detection
o Risk management
o 360- degree view of the customer
• Telecommunications
o Churn prediction
o CDR processing
o Network monitoring
• Retail
o 360- degree view of the customer
o Click-stream analysis
o Real-time promotions
• Law enforcement
o Real-time multimodal surveillance
o Situational awareness
o Cyber security detection

5. TECHNOLOGIES AND TOOLS USED
 Technologies
o Massively parallel processing (MPP) databases
o Distributed file system
o In memory computing, etc.
 Tools
o Big Data by IBM
o Exadata by Oracle

6. BUSINESS BENEFITS
 Detect, prevent and remediate financial fraud
 Calculate risk on large portfolios
 Execute high-value marketing campaigns
 Improve delinquent collections

7. THANK YOU