PURSUING THE AGILE ENTERPRISE:

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1 PURSUING THE AGILE ENTERPRISE: How a Unified Analytics Strategy Can Drive Business Value EXECUTIVE SUMMARY Agile enterprise isn t just another buzzword. There s not an organization on earth that wouldn t want to achieve faster time to market, lower costs, higher business value, better use of human capital, and greater responsiveness to changes in the market. These are all benefits of true business agility. Greenplum believes that all of these benefits stem from one key ability: the ability to make decisions quickly based on insights derived from enterprise data. But today s data stores are growing exponentially. Many of them now qualify as big data a term that loosely describes any data store that has grown large enough to force changes in the way its organization manages, uses, and disposes of it. If you want an agile enterprise, you can t get there without analyzing big data Big data represents one of the greatest opportunities and challenges today s organizations face. It s the subject of countless conferences, seminars, and white papers. Leading organizations know instinctively that there is business value in big data, and that they must quickly evolve beyond traditional business intelligence (BI) by putting data analysis at the core of every decision. To put it another way, if you want an agile enterprise, you can t get there without analyzing big data. Yet we at Greenplum have heard from numerous organizations that are struggling to get started with big data analytics. Some have difficulty just storing their big data. Others manage terabytes or even petabytes of data, but struggle to derive meaningful insights from it. Greenplum realized early on that in order to analyze big data in ways that drive business value, today s organizations would need much more than ample storage and powerful relational databases. We wrote this white paper to guide you in creating an analytics strategy that leads to business value. This white paper addresses: who works with your big data. No matter what industry you re in, Greenplum believes big data analytics represents a massive opportunity for your organization. We encourage you to embrace the transformation that s necessary to get there, so that you can reap the benefits you ll achieve once you ve arrived. WHITE PAPE R

2 THE ERA OF BIG DATA IS HERE By most measures, the arthritis drug Vioxx was a major success. In its five years on the market, Vioxx topped $2 billion per year in sales and was used by 80 million patients. Why, then, was Vioxx abruptly pulled from the shelves in 2004? Start using big data analytics to generate meaningful insights from your data The answer is big data analytics. between 1999 and 2003, there had been more than 27,000 myocardial infarction and sudden connecting clinical and cost data for a statistically valid population of cases, which generated a dataset that showed the correlation between the use of Vioxx and elevated risk of heart attacks. 1 Analyzing data effectively isn t always a matter of life or death. But it may very well mean the difference between a flourishing organization and a slow unraveling of your business regardless of your industry. The lesson? You need to start using big data analytics to generate meaningful insights from your data. If you don t, you may very well get left behind. We used to get data by people typing it. Data was a manual product. Now, it comes out of software logs and hardware centers. Data is being manufactured. I like to call this the industrial revolution of data because data is being produced by machines rather than hand crafted. When data is this easy to get, and so cheap to store, every organization can and should be getting value out of their information. Joseph Hellerstein Chancellor s Professor EECS Computer Science Division University of California, Berkeley THE ORIGINS AND IMPLICATIONS OF BIG DATA Your organization probably has no shortage of potential data sources. The modern world is churning out more data day by day. IDC recently reported that: data creation has increased ninefold in just five years. 2 Some of this data is structured operational data, which is housed in databases and often serves as raw material for BI activities. As the volume of structured data has grown, analytical databases have matured and continue to deliver better and better analytics on structured data. Thus, if businesses only needed to analyze structured data, big data would hardly seem to be a major challenge. But that s not the case. Although some big data is structured, most of it is not. For example, semi-structured data which doesn t conform to relational databases but may contain tags or other markers and unstructured data which typically comes in the form of files are growing exponentially. The bottom line is that organizations seeking true business agility need a way to analyze all of this structured and unstructured data. That is a challenge that exceeds the capabilities of relational database management systems (RDBMS). Will companies rise to meet this challenge? According to a recent TDWI survey, 70 percent of database professionals called big data an opportunity rather than a problem. 3 But although nearly three-quarters of organizations surveyed have adopted some form of analytics, only 34 percent are actually performing big data analytics. 4 The idea of big data analytics is steadily catching on but companies that adopt today still have a chance to be ahead of most of their competitors. GETTING STARTED WITH BIG DATA ANALYTICS There s more good news: most companies have a head start on the opportunity of big data analytics. If your organization has built analytics processes, you ll be able to maintain many of your best practices as you work with increasingly larger data sets. 1 McKinsey Global Institute. Big data: The next frontier for innovation, competition, and productivity. McKinsey&Company. June Russom.

3 Most companies have a head start on the opportunity of big data analytics The Greenplum Unified Analytics Platform (UAP) gives organizations the freedom to: insight from data across and beyond the organization. loading capabilities. unstructured, and machine-generated data. performance than with traditional methods. from compliance and process requirements. share results with the data science team. global support in one package. partners for business intelligence, analytics, capabilities. But because big data is fundamentally different from other data, you will need to store, process, and analyze it differently. You ll need to use new technologies that can harness the power of big data analytics alongside an existing BI and data warehousing platform. As big data has proliferated, it has become apparent that organizations need a way to bring all structured and unstructured data together as quickly and efficiently as possible based on the demands of specific analytical tasks. To get the most out of their big data, organizations need to eliminate the complexity from big data analytics and improve user productivity. INTRODUCING THE GREENPLUM UNIFIED ANALYTICS PLATFORM: THE ANSWER TO AGILE co-processing of structured and unstructured data with a productivity engine that empowers sharing of the insights that lead to greater business value. Many technology vendors think of big data as a database issue. Despite our heritage as a main components: We deliver these components over your favorite commodity hardware, cloud infrastructure, or on the Greenplum Data Computing Appliance (DCA). The modular DCA is the first best step to agile unified appliance. The DCA delivers rich facilities for redundancy, availability, fault detection, and alerting, enabling you to avoid the integration and maintenance tasks that typically reduce productivity of data science teams. The Greenplum Unified Analytics Platform Success with leveraging data and analytics to uncover business value and achieve business agility requires co-processing of structured and unstructured data and a collaborative environment to empower the people who work with the data to deliver insights.

4 GREENPLUM CHORUS: Maximize Productivity for the Data Science Team Greenplum Chorus enables big data agility for your data science team. The first solution of its kind, Chorus provides an analytic productivity platform that enables the team to search, explore, visualize, and import data from anywhere in the organization. It provides rich social network features that revolve around datasets, insights, methods, and workflows, allowing data analysts, data scientists, IT staff, DBAs, executives, and other stakeholders to participate and collaborate on big data. Customers deploy Chorus to create a self-service agile analytic infrastructure; teams can create workspaces on the fly with self-service provisioning, and then instantly start creating and sharing insights. Chorus breaks down the walls between all of the individuals involved in the data science team and empowers everyone who works with your data to more easily collaborate and derive insight from that data. GRENPLUM DATABASE: Analyze Structured Data Greenplum Database supports the next generation of big data warehousing and large-scale analytics processing, allowing you to leverage decades of structured data stored in relational Greenplum Database is engineered for business intelligence and analytical processing. In this architecture, each server node acts as a self-contained database management system that owns and manages a distinct portion of the overall data. The system automatically distributes data and parallelizes query workloads across all available hardware, leading to dramatically faster performance. GREENPLUM HD: Analyze Unstructured Data massive amounts of data. Developed in response to the growing number of companies that seek new insights from massive volumes of calls, tweets, s, pictures, and video, Greenplum solution for unstructured data. Engineered for Co-Processing with Greenplum gnet The ability to find new opportunities without designing new platforms at each step is of great far broader array of problems without platform redesign. This flexibility is made possible by Greenplum gnet, a high-speed, massively parallel integration framework between Greenplum unstructured and semi-structured data from external sources alongside structured data from the Leverage Existing Practices, Tools, and Methodologies way they ve always worked. A unified data access and query layer combines your analysts can continue working with the data integration and analysis tools of their choice, including SAS, R, MicroStrategy, and Informatica. You can also benefit from the best-of-breed offerings within Greenplum s partner ecosystem.

5 Case Study: Healthcare Company A major healthcare provider wants to innovate with big data, but its legacy system only allows it to analyze a small body of summary information. After implementing a unified big data analytics platform, the company can suddenly analyze greater amounts of diverse data, including everything from drug interactions to any individual s personal medical history. Analytics allow the company to better cluster results while adding more factors. Seeking to further enhance its care, the company turns next to analyzing external unstructured data. Leveraging all of this data, the company increases the quality of its care significantly. Not only does this enable innovative health care, but it also provides a foundation for personalized medicine. platform s openness and flexibility will allow you to integrate new tools or methods for the data analysis tasks of the future even if they haven t been envisioned yet. IT REQUIRES MORE THAN JUST TECHNOLOGY Greenplum is committed to supporting the discipline of data science which is so new that it doesn t even have an official definition. We agree with the commentator who succinctly suggests, Data science enables the creation of data products. Despite the newness of their field, data science teams are already helping their organizations do amazing things with big data. It s important to understand that data science teams are merely an evolution of the existing BI practices within today s organizations. Many of the members of an established BI practice can be critical contributors to a greater data science team. To complete the transformation from BI to data science, organizations need only add the leadership of a data scientist, who is typically an expert in statistics and has skills in software development and distributed systems. The successful data science team will also embrace line-of-business owners who will consume the final data products and implement agility. Greenplum Is Committed to Data Science We understand that big data analytics requires more than technology. That s why we re committed to the advancement of the data science discipline. We collaborate regularly with We re also investing in the community. With the help of several partners, we recently announced enterprise quality at scale. In addition, we continue to evangelize the practice of data science by creating and hosting events such as the Data Science Summits. Greenplum s Data Science Team analytic tools and business objectives, the Greenplum Data Science team works with customers daily, advancing their projects and enabling them to make new discoveries from their big data. This team is not meant to be a replacement for your existing resources; instead, it comprises data science experts who work with organizations and real data to quickly uncover significant business value. The Evolution of Enterprise Data Roles Implementing a unified analytics platform won t render your current BI staff obsolete. On the contrary, it will provide you with a framework for getting more out of all your data analytics team members, including: CONCLUSION: HOW TO GET STARTED ON THE PATH TO BUSINESS VALUE and agile and mainstream business is starting to recognize what Internet companies have already figured out: how to extract business value and monetize vast amounts of data. What enterprise wouldn t want that? That s why we re seeing the current rush to do more with big data. Data is the common element that drives the convergence of business and IT. To take advantage of the big data era, organizations need to become data-driven and evolve beyond BI to leverage high-performance data analytics that will enable them to gain greater insight and value from their data than ever before. But the biggest challenge most organizations face is resistance to change. This is human nature. There s plenty of excitement about big data, but for the majority of enterprises and organizations, changing the status quo will be difficult. To help you get started with big data

6 analytics, we ve developed a powerful set of Greenplum Analytics Labs. These unique labs are packages of services, training, and, in some cases, hardware and software, offered by Greenplum s team of leading data scientists. Our team partners with your analysts, data platform administrators, and business leadership to solve your top business challenges and find new opportunities in your data on your specific timeframe. GET STARTED TODAY WITH GREENPLUM ANALYTICS LABS Your organization can achieve true business agility, and can use the insights from big data are three steps you can take: Learn more about the world s first unified analytics platform for big data by visiting Discover Greenplum Analytics Labs by visiting the product center at Try Greenplum for yourself. Give your data science teams a chance to try out community CONTACT US To learn more about how EMC Greenplum products, services and solutions can help you realize big data opportunities visit us at Division Headquarters 1900 South Norfolk Street San Mateo, CA Tel: ABOUT EMC GREENPLUM Greenplum, a division of EMC, is driving the future of big data analytics with breakthrough products that harness the skills of data science teams to help global organizations realize the full promise of business agility and become data-driven, predictive enterprises. The division s products include Greenplum Unified Analytics Platform, Greenplum Data Computing Appliance, Greenplum Database, Greenplum Analytics Lab, Greenplum HD and Greenplum Chorus. They embody the power of open systems, cloud computing, virtualization and social collaboration enabling global organizations to gain greater insight and value from their data than ever before possible. WHITE PAPE R 2