This document provides information about a presentation on generating actionable consumer insights from analytics given at Insight Valley Asia 2013 in Bangkok, Thailand. The presentation discusses trends in information and data sources, challenges in implementing big data and analytics, opportunities in using richer data sources, and use cases in healthcare and telecommunications including customer care, genomic analysis, and high performance analytics. The presentation also reviews security challenges in big data implementation.

1. Insight Valley Asia 2013 | May 16 & 17 | Bangkok, Thailand | www.insightvalley.com

2. Insight Valley Asia 2013 | May 16 & 17 | Bangkok, Thailand | www.insightvalley.com
Thank you to our sponsor & partners!
Gold Sponsor
Supported by
Organised by

3. Generating actionable consumer
insights from analytics
Shazri, researcher from tmrnd
mshazri@gmail.com

4. talk roadmap
information & data sources trends
challenges and roadblocks in big data and
analytics implementation
opportunities too
use cases in health and telecommunication

5. information and data sources trend
more powerful tabs - increased data vol. per
person.
more real time network elements reporting
unstructured and structured relational sources

6. challenges and roadblocks in big data and
analytics implementation

7. challenges and roadblocks in big data and
analytics implementation
different db sources have different
owners, - to target higher level of
analytics abstraction.
interfacing with unstructured
sources speed
demand of output speed
security ?

8. Zoom in - Security
The following lists the security challenges in Big Data. The list was taken from Top Ten Big Data Security and
Privacy challenges, by Cloud Security Alliance.
• Secure computations in distributed programming frameworks
-Untrustworthy data mapper.
• Security best practices for non-relational data stores
-No in database security yet, now depends on middleware.
• Secure data storage and transactions logs
-No tier-ing strategies to differentiate type of data.
• End-point input validation/filtering
-Veracity, how do you make sure data is trustworthy.
-many factor validation/verification.
• Real-time security/compliance monitoring
-what is anomalous in Big Data framework.
-baseline signature?
• Scalable and composable privacy-preserving data mining and analytics
-some analytics results can be correlated with other external results that can infer identity.
• Cryptographically enforced access control and secure communication
-access must be encrypted.
• Granular access control
-Giving access to the right people, without being too troublesome.
• Granular audits
-What happened? When?
• Data provenance
-Meta data security and speed of processing.

9. opportunities too
md:more organic and whole measures map to
objective function
nw:richer outputs
nw:high velocity outputs
lg:cross web-app , mobile-app , local & secured
sources search.

10. use cases in health and
telecommunication
t:call centre - customer care and management
h:genomic analysis
t:high performance analytics and security

11. thanks
any questions ?

12. Insight Valley Asia 2013 | May 16 & 17 | Bangkok, Thailand | www.insightvalley.com
Thank you to our sponsor & partners!
Gold Sponsor
Supported by
Organised by

13. Insight Valley Asia 2013 | May 16 & 17 | Bangkok, Thailand | www.insightvalley.com