Zettaset
Big Data Ecosystem Discussion Guide
Jim Vogt, President & CEO, Zettaset
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
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
•
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
Big Data Adoption Barriers
•
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.
6
Security is #1 Technology Challenge Facing
Organizations with Big Data Initiatives*
* Source: IDG Enterprise Big Data Study, 2014
Data Security: Key to Accelerating Growth*
* Source: OvumSecurity 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
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
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
Source: CSC
Data security, reliability, and performance remain key enterprise requirements,
no matter where or how Big Data / Hadoop is deployed
•
Each of these attributes represents a challenge for organizations driving Big
Data initiatives
Five Most Important Attributes of a
BI / Analytics / Big Data Solution*
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.”
•
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
Mul+-‐Na+onal Financial Services Organiza+on
• Automate and simplify Hadoop installa+on and cluster expansion/scalability • Easy integra+on with Ac+ve Directory security policy, and data access control • Simplify and secure Hadoop connec+vity to BI and analy+cs applica+ons
Major Healthcare Provider
• Secure protected health informa+on and pa+ent records
• Assist with HIPAA compliance, lock down sensi+ve data with encryp+on • Automate administra+on and security across mul+ple loca+ons
Leading Online Payments Company
• Fine-‐grained, role-‐based access control and support for mul+-‐tenancy • High availability and automated fail-‐over for on-‐demand service reliability • Ac+vity monitoring and logging for SLA repor+ng
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
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
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
