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

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

Thank you to our sponsor & partners!

Gold Sponsor

Supported by

Organised by

Generating actionable consumer

insights from analytics

Shazri, researcher from tmrnd

mshazri@gmail.com

talk roadmap

information & data sources trends

challenges and roadblocks in big data and

analytics implementation

opportunities too

use cases in health and telecommunication

information and data sources trend

more powerful tabs - increased data vol. per

person.

more real time network elements reporting

unstructured and structured relational sources

challenges and roadblocks in big data and

analytics implementation

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 ?

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.

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.

use cases in health and

telecommunication

t:call centre - customer care and management

h:genomic analysis

t:high performance analytics and security

thanks

any questions ?

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

Thank you to our sponsor & partners!

Gold Sponsor

Supported by

Organised by

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