1. Future of Data : Big Data
Shankar Radhakrishnan
Cognizant

2. Topics
 How did we get here ?
 Data Explosion
 Big Data
 Big Data in an Enterprise
 Big Data Platform - Hadoop
 Big Data Adoption
Q&A

3. How did we get here?
 Familiar World
Data Integration Problems
 EDW
 Datamarts Data Processing Problems
 Familiar Problems Data
warehouse
Storage Management
Performance Problems
Limitations out of Complexity
 New World
 Newer type of data to integrate
 Increase in volume
 Newer analytical requirements

4. Data Explosion

5. Newer Interests
 Social Intelligence
 DBIM, Sentiment Analysis, Social Customer Care
 Predictive Analytics
 Propensity, Price Elasticity, Anti-Fraud Analytics
 Segmentation Insights
 Funnel Analysis, Behavioral Patterns, Cohort Analysis
 Mobile Analytics
 Ad-Targeting, Geo-spatial Analytics

6. Categories
 Structured Data
 Enterprise Data (CRM, ERP, Data Stores, Reference Data)
 Semi-structured Data
 Machine Generated Data (Sensor Data, RFIDs)
 Unstructured Data
 Social Data (Comments, Tweets), Blog posts

7. Big Data
“Big Data” refers to high volume, velocity, variety and complex information assets that
demand cost-effective, innovative forms of information processing for enhanced insight
and decision making

8. Big Data Platforms
• Data Integration
o Informatica, Infosphere
o talenD, Pentaho, Karmasphere, Apache Sqoop, Apache Flume
• Database Framework
o Hadoop (Distributions: Cloudera, Hortonworks, MapR)
o Hbase
o Hive
• NoSQL Databases
o MongoDB, CouchDB
• Machine Data Processing
o Splunk, Mahout
• Text Analytics
o Clarabridge, Lexanalytics

9. Big Data in an Enterprise
Big Data Big Data
ETL
Sources Platform
Datamarts
ETL Analytical
Datamarts Applications
Datamarts
Data ETL Data warehouse
Sources

10. Hadoop - Ecosystem

11. Big Data : Adoption Drivers

12. Big Data – Adoption Scenarios
 Replatforming to Big Data (Hadoop, MapR)
 Archival Solution (Hadoop)
 Offloading Data warehouse, EDW (Hadoop, Hive)
 Social Media Integration
 Machine Data Analysis (Splunk, Mahout)
 Complex Analytical Requirements (Hbase)

13. Q&A