How To Grow A Data Center System

Transcription

1 Zettaset Big Data Ecosystem Discussion Guide Jim Vogt, President & CEO, Zettaset June 20, 2014 The informa,on provided in this document cons,tutes confiden,al and proprietary informa,on of Ze8aset, Inc. You may not disclose, use, reproduce or distribute this document (or any por,on thereof) without Ze8aset's prior wri8en authoriza,on. Further, as between you and Ze8aset, Ze8aset owns all right,,tle and interest in and to this document (together with any and all related intellectual property rights).

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 Hadoop Emerging as Primary Data Store 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

5 Big Data Adoption Barriers Security for big data will be a key issue in 2014 and beyond. Merv Adrian, Gartner blog - March 2014 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 5

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

7 Data Security: Key to Accelerating Growth* Number of respondents with concerns about big data issues * Source: Ovum Security controls used to protect against insider attacks by number of respondents Percentage responses for the top three cloud and SaaS usage concerns Lack of control over the location of data Potential for other users of the service to access my organization's data Lack of visibility into the security measures used by the SaaS or Cloud Provider 55% 57% 59% 0% 20% 40% 60% 80% 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 7

8 Big Data Highly Services Dependent* * 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 * Source: Wikibon, February 2014

9 Synergy Between Big Data and Cloud Data security, reliability, and performance remain key enterprise requirements, no matter where or how Big Data / Hadoop is deployed 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 ondemand, any time, anywhere Source: CSC 9

10 Five Most Important Attributes of a BI / Analytics / Big Data Solution* Each of these attributes represents a challenge for organizations driving Big Data initiatives * 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 What Analytics Users Want in a Big Data Solution 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

13 Enterprise Requirements Examples 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 13

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 ondemand, 24 x 7 Requirement to secure one merchant s data from the data of others, and that requires multitenancy, supported by sophisticated role-based access control

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