I D C V E N D O R S P O T L I G H T. S t o r a g e Ar c h i t e c t u r e t o Better Manage B i g D a t a C hallenges

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1 I D C V E N D O R S P O T L I G H T S t o r a g e Ar c h i t e c t u r e t o Better Manage B i g D a t a C hallenges September 2012 Adapted from Worldwide File-Based Storage Forecast: Foundation Solutions for Content Delivery, Archiving, and Big Data by Richard L. Villars and Eric Sheppard, IDC # Sponsored by Actifio "Big Data" offers the promise of exciting new business insights and powerful new business capabilities. However, storing Big Data in a way that maintains access, protection, and business continuity presents a new and daunting set of real-life challenges, especially for organizations struggling to keep up with the data storage explosion already under way inside the enterprise. This Vendor Spotlight examines the unique challenges of Big Data protection and availability storage in the context of underlying forces driving the data storage explosion. The primary role of "copy data" referring to the excessive copies of production data created by independent business systems such as backup, snapshot, disaster recovery, business continuity, test and development, analytics, information sharing, and even compliance systems in these challenges is explored. The paper highlights the increasing importance of adopting new storage architectures capable of boosting the efficiency and reliability of collecting, storing, analyzing, protecting, and delivering this vital information. The role of storage vendor Actifio is also highlighted in terms of this strategically important market. The Root Cause of the Big Data Explosion The convergence of intelligent devices, social networking, pervasive broadband networking, and analytics ushers in a new, "intelligent economy" that is generating a constant stream of what is commonly referred to as Big Data. Big Data grows even bigger with legacy siloed data management systems currently in place throughout most enterprises, including backup, snapshot, disaster recovery, and test and development. Each siloed system creates and stores its own copy of data, accelerating the amount of expensive production storage required. Big Data typically encompasses different data types (structured, semistructured, and unstructured) from a variety of data sources (typically both internal and external to an organization). Two kinds of data are driving the storage explosion inside businesses: Production data, which is the real-time data created and used by business applications Copy data, which is the data created by all the business systems that make a copy of everything in production Organizations ranging from small and medium-sized businesses (SMBs) to large enterprises in every industry are increasingly relying on this combination of structured and unstructured data to make more informed and better strategic business decisions and to gain competitive advantage and improve operations. An example of the type of information that can be gleaned from this approach is the mashup of internal operational data from an ERP system with semistructured data from Web log files that identifies customers' online behavior, with sentiment analysis of unstructured text from customer comments. IDC 1367

2 One cannot underestimate the growing importance of collecting and analyzing Big Data to the success of an organization and its ability to compete effectively. Organizations that are best able to make real-time business decisions using Big Data will thrive, while those that are unable to embrace and capitalize on this shift will increasingly find themselves at a competitive disadvantage in the market. For example, Big Data is being captured and analyzed to facilitate many critical lines of business, including the following: Customer relationship management (including sales, marketing, customer service) Supply chain and operations Research and development IT management Risk management Some common sources of this data and some typical applications are as follows: , collaboration tools, social media, and Web sites for communicating and conducting business with prospects, customers, and business partners Collection, storage, and analysis of ever-increasing amounts of information to create more compelling products, increase customer sales and retention, and increase speed of transactions Digitized records, design documents, and other types of unstructured data to boost efficiency, offer new services, and comply with changing government regulations IDC expects the Big Data technology and services market to grow from $3.2 billion in 2010 to $16.9 billion in This represents a compound annual growth rate (CAGR) of 39.4%, or about seven times that of the overall information and communication technology market. In addition, the IDC storage consumption model shows traditional structured production data growing in terms of capacity at a 22.5% CAGR between 2011 and 2016, while replicated/copy data will grow at a 27% CAGR over the same forecast period. The consequences of the escalating importance of Big Data are that there's too much information in too many formats to assimilate and too many changes occurring too rapidly for traditional tools and technology to keep pace. This is all happening at a time of increasing demand on organizations to respond faster and with greater insight to ongoing internal and external events. Because of Big Data's strategic value to organizations, higher priority is being placed on boosting the efficiency and reliability of IT platforms for copy data management (collecting, storing, analyzing, protecting, and delivering this information). However, given how large and how fast these data sets grow, Big Data is creating complex technical and infrastructure challenges for organizations and service providers alike while posing a number of challenges for IT and storage administrators who are still relying on traditional or outdated technologies to perform these tasks. These technologies include backup software and platform-specific tools such as production array-based snapshots and replication. Traditional storage systems that are designed to store real-time data are not efficient when data is collected by multiple tools, and this often results in the creation of multiple copies of Big Data. This is the root of the problem. According to some reports, production data is growing at 8% versus the geometric growth of copy data. In addition, older technologies cannot handle this scale of data volumes; they frequently create redundant silos of IT infrastructure and data management applications. As a result of the inadequacies of older technologies, companies are continuously struggling to ensure that data is protected and recoverable to meet business needs IDC

3 Storage architectures, managed services, cloud services, and analytical tools are still works in progress in terms of their evolution and their ability to more cost effectively and efficiently manage, secure, serve, and archive Big Data. Today, the term Big Data also refers to the collection of newer technologies that can handle data volumes well beyond the capabilities of older, traditional technologies. Many hardware resources leverage an approach made possible through advances in the development of server clusters as processing grids, system and storage resource virtualization, the utility computing paradigm supported by dynamic provisioning software, and declining storage prices that make large-scale data redundancy affordable (although this is not always desirable). Some Big Data technologies are reworked versions of technologies that had not provided Big Data capability in the past, such as relational database management systems (RDBMSs). Others represent the application of old, well-established data management algorithms formerly used in simple, limited data management contexts to the problem of managing explosively growing data in the cloud. Some vendors apply techniques such as sharding, massive parallelism, and peer-to-peer clusterbased cooperative processing, resulting in a new capacity to collect very large amounts of data in a much more flexible, dynamic, and scalable way and to query, search, maintain, and perform analytic operations against that data. In addition, some managed service providers, cloud service providers, and application service providers are able to deliver many of the critical Big Data management services and additional on-demand services for Big Data such as disaster recovery, business continuity, backup, data access, and more. Benefits of Using Storage Architectures Optimized for Copy Data Management To meet the challenges associated with Big Data, many organizations and service providers are adopting an IT infrastructure and strategy that optimizes their server, storage, and network resources. Some storage architectures are more attuned to delivering the cost efficiencies, performance and scalability, agility, accessibility, and data protection required for Big Data projects. Some storage architectures can also provide many, if not all, of the following benefits: Support reliable and faster access to significantly more and larger files for much longer periods of time as well as ensure both cost-efficient and secure retention and sharing of content Cost-effectively handle specific data variety, volume, and velocity challenges without compromising speed or access to available knowledge within the data Provide improved support for always-on operations as well as disaster recovery on demand Eliminate the inefficiencies and complexities that are burdening managers across a wide range of organizations Utilize infrastructure consolidation and application reconciliation initiatives that reduce cost and can increase resource utilization Utilize server virtualization technologies that can execute data protection policies without incurring additional infrastructure penalties, duplicating efforts, or retaining granularity of recovery Manage virtual machine sprawl and avoid the duplication of data being stored Monetize the value of unstructured data through more sophisticated business intelligence and analytics solutions 2012 IDC 3

4 Key Technology Trends The growth in appliances as well as cloud and outsourcing products and services for Big Data technology will likely mean that over time end users will pay increasingly less attention to technology capabilities and will focus instead on the business value arguments. System performance, availability, security, manageability, and business continuity will continue to be of great significance to all organizations. However, how these business directives are achieved will be less of a point of differentiation among vendors. The growth in opportunities for Big Data technology will likely mean that end users will choose new applications and services based more on the business value they deliver than on the technology itself or the format in which the data is delivered (SQL, spreadsheets, etc.). Considering Actifio Founded in 2009, Actifio is based in Waltham, Massachusetts, and is focused on delivering nextgeneration data management and storage solutions. Actifio's current business model and product line grew out of the need to effectively address the challenges around managing copies of data and replacing backup software, particularly when siloed array-based tools (snapshot, replication) are used for data protection, business continuity, and disaster recovery. Actifio has evolved from applying virtualization to data management to transforming data management into a virtualized service to help enterprises solve the problems associated with trying to manage massive amounts of Big Data on application hosts. Organizations use Actifio's solutions to decrease the time required to complete a backup as well as reduce both the number of resources a backup consumes and the costs associated with ensuring business continuity and disaster recovery. In addition, organizations can reduce or eliminate redundant processes and copy data that are created by traditional storage technologies. Based on Actifio's patented Virtual Data Pipeline (VDP) technology, the Actifio Protection and Availability Storage (PAS) product is a scalable, service level driven storage platform that can be used by any business application. PAS seeks to simplify the processes traditionally used for backup, disaster recovery, business continuity, compliance, analytics, and test and development by eliminating redundant silos of data and applications. Designed as a simple, application-centric, policy-driven solution that decouples data management from the storage, network, and server infrastructure, PAS is designed to eliminate vendor lock-in. This design also alleviates many of the challenges associated with managing exploding data growth. Based on current deployments, the company claims it can deliver a 10x reduction in costs while enhancing business availability and improving storage efficiency. The company also reports that it has been able to reduce storage costs by 90% and network utilization by 70% for some customers. Additional PAS features and benefits include the following: Utilizes a simple user interface for operational ease of use Provides protection and recovery of information instantly, with no more than three clicks at any location, for any application for any IT environment Is intended to meet individual enterprise IT and managed or cloud service provider's protection and availability requirements in physical, virtual, or hybrid IT environments through a combination of the PAS architecture, virtualization, and multiple packaging options Optimizes the management of data history and copies by storing data and metadata in a single, service-oriented solution IDC

5 Delivers instant, incremental data capture and restore in an optimized storage and network footprint Reportedly reduces TCO by eliminating the need for multiple licenses and reducing storage and network bandwidth costs Actifio's PAS platform has been implemented by managed service providers, cloud service providers, and organizations frustrated by the management challenges associated with Big Data. Actifio is expanding its operations globally and increasing awareness of its ability to enable transformation of the datacenter into an SLA-driven services organization. The PAS platform has recently been expanded to address test and development, analytics, compliance, ediscovery, and other businesscritical requirements, creating a new category of storage that efficiently virtualizes and manages copies of production data. Actifio is also focused on reaching the broadest market through strategic partners and value-added resellers (VARs). Because one of those partners is IBM, Actifio PAS was also designed to work with IBM storage systems along with other storage vendors including EMC, HP, NetApp, and Dell. Working together, Actifio and IBM are marketing the solution to service providers and VARs worldwide and expect that this solution will be well suited for services such as cloud-based data backup. Challenges There are challenges for Actifio, however. Big Data projects typically require lots of players, technologies, skills, and integration. Actifio's technology and support must work well as part of a larger solution. Also, despite having large partners such as IBM, Actifio must continue contending with the challenge of being a smaller, innovative firm competing with larger Big Data and storage rivals. Conclusion The Big Data explosion and the technologies currently used to store, process, and manage the data will transform organizational agility. However, the process of collecting, storing, and managing this data is fraught with challenges and frustrations for organizations. No matter how big or how small the organization, information overload is an unmanageable problem. Increasingly large streams of Big Data that promise to provide organizations with a greater understanding of their business instead require organizations to invest a significant amount of money and effort just to stay on top of the data. This is in addition to the work involved in making sure that the data that is collected, stored, secured, managed, and delivered can be quickly recovered and conforms to regulatory standards and policy requirements. IDC's recent surveys show that the information access market is restive customers want highly integrated software stacks to aggregate, access, manage, analyze, and deliver information in a unified manner across all their sources. This calls for new architectures more attuned to and capable of managing and understanding Big Data and its requirements. Organizations that want to capitalize on the new trends involving cloud, mobility, social business, and Big Data technologies will certainly look more closely at assessing and acquiring new storage solutions to gain more systems performance, operational efficiency, and data management intelligence. IDC believes the Big Data market will continue to experience strong growth in the years ahead. If Actifio can address the challenges described in this paper and deliver the business benefits organizations utilizing Big Data require, the company has a significant opportunity for success in this market IDC 5

6 A B O U T T H I S P U B L I C A T I ON This publication was produced by IDC Go-to-Market Services. The opinion, analysis, and research results presented herein are drawn from more detailed research and analysis independently conducted and published by IDC, unless specific vendor sponsorship is noted. IDC Go-to-Market Services makes IDC content available in a wide range of formats for distribution by various companies. A license to distribute IDC content does not imply endorsement of or opinion about the licensee. C O P Y R I G H T A N D R E S T R I C T I O N S Any IDC information or reference to IDC that is to be used in advertising, press releases, or promotional materials requires prior written approval from IDC. For permission requests, contact the GMS information line at or Translation and/or localization of this document requires an additional license from IDC. For more information on IDC, visit For more information on IDC GMS, visit Global Headquarters: 5 Speen Street Framingham, MA USA P F IDC

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