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1 I D C T E C H N O L O G Y S P O T L I G H T Capitalizing on the Future with Data Solutions December 2015 Adapted from IDC PeerScape: Practices for Ensuring a Successful Big Data and Analytics Project, by Carl W. Olofson, IDC # Sponsored by Dell Harnessing the power of big data and analytics (BDA) to improve data-driven decision making is the hallmark of an organization that embraces the future. Yet many organizations that need to become "future ready" lack the competency or maturity to address the range of BDA process, staffing, and technology requirements. Along with the opportunity to unlock the value of BDA to accelerate innovation, drive optimization, and improve compliance comes the need to demonstrate value, navigate expanding technology alternatives, re-create business processes, and ensure the availability of appropriately skilled staff. This Technology Spotlight examines what it takes organizationally to become future ready and gain the most benefit from BDA. The paper also looks at the role of Dell in the strategically important market of BDA, and offers best practices for BDA project creation and ongoing usage. Introduction: Why Being "Future Ready" with BDA Matters Big Data and analytics (BDA) is critical for organizational innovation and transformation. It allows organizations to capture insights from and better monetize their data by getting the right information to the right individuals at the right time. Organizations depend on data to drive new sources of competitive differentiation as well as support ongoing business processes. But finding the best ways to leverage BDA for greater operational efficiency and discovering new business opportunities is challenging. It raises the question of whether an organization is ready for this form of digital business. In today's digital economy, business success or failure ties directly to the effectiveness and timeliness of an organization's IT service delivery. Organizations with the most effective and timely IT service delivery are what IDC calls "future ready." These organizations are always extending the abilities of their IT infrastructure and applications, while also pursuing IT practices that enable them to identify and address changing business and technology needs. A recent IDC study quantified the extent to which future readiness matters in today s digital business world. IDC identified four levels of enterprise future readiness: Future Creators, Future Focused, Future Aware, and Current Focused. The more future ready the organizations in our study were, the stronger their business outcomes. Future Creators, the most future-ready organizations, outperformed all other groups and significantly outperformed Current Focused in a wide variety of business metrics. Big data and analytics was no exception. While many organizations use BDA in some way, the most future-ready organizations are seeing the biggest business benefits (see Figure 1). IDC 2033

2 F i g u r e 1 Big Data Benefits N=43 for Future Creator, N=23 for Current Focused Source: IDC's Future-Readiness Enterprise Study, June % of Future Creators cite better ability to predict events or outcomes as a significant benefit of Big Data and analytics compared with 34% of Current Focused. 52% of Future Creators cite faster reaction time to external events versus 38% of Current Focused. Future Creators have made strategic decisions about BDA that enable them to realize these benefits. For example, 57% of Future Creators have a single BDA strategy across the entire enterprise, while only 38% of Current Focused have a single BDA strategy. Future Creators also set themselves apart by providing access to big data and analytics across all levels of the organization, from executives to operational staff. By giving BDA access to operational staff (90%), Future Creators are democratizing data and making it available for decision making across the enterprise. This is the biggest difference between Future Creators and Current Focused only 21% of Current Focused organizations in our study provided BDA access to operational staff to a significant extent. Best Practices for BDA Success So how do organizations reach the Future-Creator level of BDA skills and outcomes? They start by answering the following questions: What kinds of data are available to be leveraged? Which technology is the right one for the job? Do we have the skills to tackle the task? How can we keep delivering value going forward? 2015 IDC 2

3 These questions represent critical practice areas that will enable enterprises to initiate and gain maximum value from BDA projects. Adhering to the practices described in this paper will ensure that an organization's BDA efforts result in ongoing enhanced business intelligence, and are agile enough to respond to ever-changing market needs. Best Practice: Identify the Types of Data to Be Leveraged Before starting a BDA project, a team should identify data to be collected and managed or analyzed. This can be data that is present but not currently collected or managed in any way or it could be data that is managed inappropriately. The data in question can be any data, including that which is not derived from, or managed through, standard transactional applications. It may come from external sources, such as streaming data from partners or the Internet of Things (IoT), or from internal sources including such things as s that reveal customer sentiment or help desk data that can be used to determine the efficiency of problem resolution (a key to customer retention) or to identify endemic product defects. Increasingly, enterprises are either developing cloud-based applications for customer self-service applications or subscribing to software-as-a-service (SaaS) applications of this kind. These applications often capture details about how the customer traversed the site, what was selected and deselected, how long the interaction took, and so on. Best Practice: Determine Business Benefits to Be Derived from the Data Once the data to be analyzed has been identified, it would seem that the business benefits of working with that data are obvious, but often they aren't. This is because the technical staff can identify and explain the data in technical terms, but they are not necessarily aware of the business meaning or value of that data. For this reason, determining the business benefits of the data requires the cooperative efforts of a combination of technical and business people. This cooperative team should look through the various kinds and types of data found, select the data having clear business value potential, and then figure out what the benefits of working with that data might be. It may also be necessary to include statisticians or data scientists in the project, since they can explain how the data may be analyzed and exploited. Developers can then determine where BDA can help enrich operational applications or even drive new ones. Best Practice: Choose the Right Technology for the Job Knowing the data and its application should lead to an investigation of which technology is right for the data at hand. Potential technologies and their characteristics are as follows: Hadoop: Best for analyzing historical data and content data Key-value store: Used for managing transitory data in applications and, sometimes, for transactional data Scalable RDBMS: In row-oriented form, used for extreme transaction processing for apps requiring speed and flexibility; in column-oriented form, used for recurring deep analysis, cumulative statistics, and selective statistics NewSQL RDBMS: Able to dynamically change database schema; also supports elastic scalability for transactional or analytical data processing Graph DBMS: Used for associative analysis and pattern recognition for apps such as physical network management (e.g., power grid or telephone network), social media network analysis for marketing, and personal association analysis for law enforcement 2015 IDC 3

4 Best Practice: Establish a Team with the Right Skill Set for the Task It's important to bring the right people to bear on the project at hand. The team might include the following: Internal IT technicians Data analysts Business managers And possibly outside consultants These people will not all engaged all the time, but each team member should have a role and points of engagement in the process. Best Practice: Align Business and IT Expectations and Efforts When a BDA project is funded with unclear objectives, then expectations cannot be managed, and everyone involved may find themselves diminished. It is important to have a rolling set of expectations, organized as a series of phases. The first phases are known, as defined by the first four practices listed here, followed by a pilot project to demonstrate the utility of the work and establish a sense of realistic timelines and costs that may be used to plan future projects. Expectations should be kept low in the beginning, as the cost and time involved in initial efforts are frequently not as wellknown as the participants think they are. After initial success, increased confidence can lead to more accurate planning and more ambitious efforts. This practice is not just about initiation, however. A rolling set of expectations that are continuously managed and regularly communicated should remain in effect as long as BDA technologies are in use. It is necessary to review existing BDA applications and their benefits on a regular basis, and compare them with the changing needs of the business. It's also necessary to compare existing technologies with new or more evolved technologies that may represent a better fit for an application going forward. BDA technology is still evolving rapidly, and new versions of technologies in use, as well as new technologies altogether, may prove the right choice not only for later projects, but also for existing applications. Considering Dell BDA Solutions Dell offers solutions encompassing four key areas of big data and analytics: Analytics & Business Intelligence, which can help run any analytics on any data, anywhere streaming or at rest to drive better decisions across the client organization. Dell's analytics expertise and secure, highly intuitive, and customizable software helps clients improve operations and customer satisfaction; simplify predictive analytics, forecasting, and data mining; and innovate "the next big thing." Data Integration, which helps eliminate fragmented analysis with a real-time view of all a client's data. Dell can reportedly integrate over 160 data sources, regardless of the underlying data platform or its location (on- and off-premises). Dell software enables clients to synchronize data between critical applications, ensure data quality across all environments, and create data mashups from multiple underlying data sources. Data Management, which helps clients develop, administer, and monitor various data platforms structured and unstructured from Oracle to Microsoft SQL Server to Hadoop to MongoDB, and more. Dell's solution is designed to help clients easily administer, monitor, back up, analyze, 2015 IDC 4

5 and troubleshoot databases while collaborating with global peers to create high-quality, performance-optimized database code. Infrastructure, which provides Dell s open, scalable architected Big Data Blueprint and infrastructure to seamlessly integrate with existing infrastructures and boost data-intensive applications, such as online transaction processing (OLTP) while scaling as client data grows and diversifies. Challenges Dell does face market challenges, however. The company must continue refining its own consulting services, and leverage its expanding network of partner services, to address the needs of customers who want to do more than just purchase technology. Dell needs to be able to provide advice about what data to track, how to analyze the data, and how to influence action and effect change based on the results of the data analysis. The company also needs to prepare for new competition from unexpected segments of the market. Retailers, financial services firms, communications providers, and others are entering the market with their own big data services that will compete with some of the services and technology Dell provides. This includes cloud infrastructure and services. Dell needs to continue articulating its value proposition by connecting cloud-based BDA service capabilities to business problems and opportunities. Conclusion Future Creators, the organizations with the highest levels of future readiness, excel in the deployment and use of big data and analytics. This excellence allows these organizations to not only quickly adapt to disruptions, but also to drive innovation. Fortunately, organizations lower on the future-readiness scale don t need to achieve the highest levels of future readiness to begin seeing improvements from BDA. Future readiness is a journey, and moving up a single level improves business outcomes regardless of an organization's starting point. Companies can also choose to focus on a BDA technology or use case most appropriate to their business needs and still see improvements. However, two elements are fundamental for success: A strategic approach to BDA that drives business decisions (versus a short-term focus on cost reduction) An IT organization that can work closely with lines of business to address the needs of the organization To the extent Dell can successfully address the challenges described in this paper, the company has a significant opportunity to help organizations achieve future readiness with big data and analytics. 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 Custom Solutions. 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 Custom Solutions 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 IDC 5

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