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Zettaset
Hadoop: Making it Work
in the Business Unit
Jim Vogt, President & CEO, Zettaset
Hadoop Summit - June 5, 2014

2. View from the Business Unit…
• Customer focus is shifting to the top layers of the big data software
stack, from information management to the “analytics & discovery”
and “applications” layers

3. Hadoop in its Infancy
• Early Hadoop adoption was driven by cost savings
• Hadoop’s value proposition to enterprise customers has expanded to include
flexibility, analytics, and discovery capabilities
• As Hadoop continues to mature, the stack of applications and business processes
that can work with data directly in Hadoop’s file system is growing, driving a virtuous
cycle of adoption
• Hadoop becoming increasingly strategic and mission critical to enterprise computing:
Potential to become the primary data management technology
3

4. • As key enterprise issues with Hadoop are addressed through
technology, Hadoop will emerge as the primary data store
• Cost-effective, powerful, flexible and secure
4
Hadoop Emerging as Primary Data Store

5. Big Data Adoption Barriers
5
• Given its relative immaturity, customers face multiple issues with
Hadoop deployments, including security, reliability, application
integration, dependence on professional services
• Lack of best practices for integrating Big Data analytics into existing
business processes and workflows
• Vendors racing to address customer challenges with new solution
capabilities
Security for big data will be a key issue in 2014 and beyond.
Merv Adrian, Gartner blog - March 2014

6. 6
Security is #1 Technology Challenge Facing
Organizations with Big Data Initiatives*
* Source: IDG Enterprise Big Data Study, 2014
Sample: 751 companies

7. Data Security: Key to Accelerating Growth*
7
* Source: Ovum
Security controls used to protect against insider
attacks by number of respondents
Number of respondents with concerns about big data issues
59%
57%
55%
0% 20% 40% 60% 80%
Lack of visibility into the security
measures used by the SaaS or
Cloud Provider
Potential for other users of the
service to access my
organization's data
Lack of control over the location of
data
Percentage responses for the top three cloud and SaaS
usage concerns
• Security in particular is a key focus for enterprise customers considering Big Data solutions
• Enterprises face severe commercial and reputational risk from data breaches
• Enterprise customers will not deploy Hadoop to manage sensitive data until vendors secure
such infrastructure

8. Big Data Highly Services Dependent*
* Source: Wikibon, February 2014
* Big Data
Revenue by
Type, 2013
(in $US millions)
(n=$18,814)
• Challenging to scale
services-based business
models
• Software projected to have
the fastest growth rate out
of the three segments
• Market will shift to software
because its value
proposition is automated
and replicable as the
technology matures

9. Synergy Between Big Data and Cloud
• Virtually unlimited data
storage scale-out
• Multiple applications and
“as-a-service” offerings
supportable
• Point of integration with
third-party data sources
• Service and capacity on-
demand, any time,
anywhere
9
Source: CSC
Data security, reliability, and performance remain key enterprise requirements,
no matter where or how Big Data / Hadoop is deployed

10. • Each of these attributes represents a challenge for organizations driving Big
Data initiatives
Five Most Important Attributes of a
BI / Analytics / Big Data Solution*
* Source: Enterprise Strategy Group - April 2014

11. Analytics Pulling the Market
“This is a time of accelerating
change, where your current IT
architecture will be rendered
obsolete.
Leading organizations of the
future will be distinguished by
the quality of their predictive
algorithms.”
- Peter Sondergaard, Gartner

12. • Comprehensive security, including access control and data encryption
• Response time not affected by security controls, no impact on user experience
• High availability ensure the reliability and stability of the database
• Data access via easy-to-use graphical user interfaces, no need to write code
• Advanced analytic capabilities to analyze multi-structured data
• Sophisticated visualizations to understand and make sense of Big Data
• “Speed-of-thought” performance, a cumulative measure of all components
What Analytics Users Want
in a Big Data Solution

13. Multi-National Financial Services Organization
•Automate and simplify Hadoop installation and cluster expansion/scalability
•Easy integration with Active Directory security policy, and data access control
•Simplify and secure Hadoop connectivity to BI and analytics applications
Major Healthcare Provider
•Secure protected health information and patient records
•Assist with HIPAA compliance, lock down sensitive data with encryption
•Automate administration and security across multiple locations
Leading Online Payments Company
•Fine-grained, role-based access control and support for multi-tenancy
•High availability and automated fail-over for on-demand service reliability
•Activity monitoring and logging for SLA reporting
13
Enterprise Requirements Examples

14. Use Case – Financial Services
• Banks and credit card companies want to be
able to analyze years of transaction history to
investigate and predict fraudulent transactions,
detect purchase patterns of consumers and
score individuals on credit worthiness
• Depth of this transactional history ranges from
hundreds of Terabytes to several Petabytes of
data, making it cost prohibitive for traditional
databases
• Hadoop proving to be a more cost-effective and
scalable storage and data access solution
• However, securing consumer financial data in
Hadoop is of paramount importance to financial
institutions, who must comply with data
protection and privacy mandates such as
PCI/DSS and SOX

15. Use Case – Healthcare Records
• Electronic healthcare records are vulnerable to
both insider and outsider threats because of the
value of information to criminals
• Physicians notes are an example of
unstructured data that is retained by healthcare
organizations
• When combined, this information represents
highly sensitive 'regulated data,' which is tightly
controlled by federal laws as well as numerous
state breach notification laws
• HIPAA - Health Insurance Portability and
Accountability Act addresses the privacy and
security of patient data
15

16. Use Case – Retail Payments
• Online payments company combines the use of
Hadoop databases with analytics for merchant
reporting, along with dashboard applications
that analyze merchant-specific payments
• Data security as well as service reliability is of
utmost importance in this environment
• Transactions involve a database that includes
personally-identifiable information for millions of
users, and the system must be available on-
demand, 24 x 7
• Requirement to secure one merchant’s data
from the data of others, and that requires multi-
tenancy, supported by sophisticated role-based
access control

17. Hadoop:
Meeting Business Unit Expectations
Focus on business applications and
processes vs. database mechanics
Comprehensive security approach that
simplifies integration with existing
enterprise security frameworks
Simplified application integration,
including analytics
High reliability across all critical
Hadoop services
More process automation, and fewer
requirements for professional services
Hadoop that’s enterprise-ready
17

18. Thank you!