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- 1. Analytics solutions for driving better business outcomes Unlock the power of Big Data for better business outcomes See why leading analytics providers rely on Cisco infrastructure to deliver business outcome solutions for their customers Count on Cisco to have the right end to end analytics ready infrastructure to support you wherever your analytics journey takes you. Three main categories of the analytics ecosystem: Key Trends in Big Data and Analytics Challenges Implementing Big Data and Analytics Solutions Data analytics Splunk, SAP, Platfora, SAS 3 Data integration Cisco® Data Virtualization 2 Data management Hadoop, NoSQL, MPP 1 Enterprises have an insatiable appetite for the insights that data provides. Data is located everywhere: data centers, apps, in the network, and at the edge. Analytics solutions are required to generate insights from data in the cloud, in the data centers, and at the edge. Big data and analytics will become pervasive throughout the enterprise. Data driven insights will become a competitive necessity. Scaling to keep pace with the growth of big data Integrating and facilitating access to data wherever it resides Generating real time insights without moving the data Maintaining low TCO with expanding data lakes and use cases Putting data into the hands of those that need it; enabling insight driven action without human intervention Cisco has a reseller agreement of Hadoop with Cloudera, Hortonworks, and MapR “Cisco infrastructure is the perfect match for Cisco Data Virtualization software. We would recommend it even if we weren’t a part of Cisco.” “As our customers expand their use of Splunk to capture and analyze trillions of real time events every day, they can help ensure rapid, predictable delivery of insights with a high performance, highly scalable Cisco UCS architecture” “The capability of Cisco UCS® management to administer systems, scale out easily, and maintain them has been a big benefit for our customers.” “Cisco UCS provides customers with the ability to do data processing and data collection at the edge, close to or on the device itself. Cisco UCS’s edge capabilities were a breakthrough for SAP.” “By putting SAS Analytics on Cisco UCS infrastructure, we can help enterprises integrate high velocity computing, networking, memory, and storage access to accelerate delivery of insights in real time.” CISCO DATA VIRTUALIZATION Process analytics anywhere An analytics ready infrastructure, and Cisco Data Virtualization drives insights everywhere, from the data center to the edge Industry’s first big data benchmark results TPCx-HS benchmark results confirm the real world performance and scalability of Cisco Unified Computing System™ (Cisco UCS) for enterprise Hadoop deployments Redefine operational efficiency • 61 percent reduction in management costs • 83 percent reduction in provisioning time • 77 percent reduction in cables and switches with Cisco UCS • Ability to manage big data and traditional RDBMS in a single environment Keep pace with the growth of big data Seamless scalability to 10,000 servers Faster time to insight Cisco Application Centric Infrastructure delivers advances in big data workload prioritization and optimization Data is the lifeblood of applications, and increasingly the lifeblood of business. Extracting insights held captive in your data requires an analytics ready infrastructure that enables a broad range of joint solutions with ecosystem partners. © 2014-2015 Cisco and/or its affiliates. All rights reserved.
- 2. CATEGORY Market trends and customer challenges • Data is the key enabler for analytics. • The more variety in the types of data you bring to bear, the more complete the analysis, and the better the business outcome. • By 2020, 40% of all data will be generated by sensors on the edge. • Business struggle to get access and use all of their data. • After data is compiled, extracting insights is often a painstakingly long process. • Insights must be accessible to business users as well as analysts and data scientists, with the ability to iterate. • Decision-making must change from intuition based to analytics based. • People expect self- service access to information in a form they can easily understand and share. • To increase speed and effectiveness, customers need a comprehensive and efficient data management foundation and strategy to make use of massive amounts of data. • Machine data is the fastest growing, most complex and most valuable segment of big data. • Many organizations struggle to gain business insights from machine data. • Traditional analytics solutions are not architected for high- volume, high- velocity, or highly diverse data. Role in the analytics ecosystem • Provides easy access to data regardless of location through a focused data virtualization solution. • Offers an analytics platform that’s native on Hadoop, fueled by the power of Apache Spark. • IDC recently identified SAS as the top supplier, owning 35.4 percent market share of the 2013 advanced and predictive analytics market, more than twice that of the next-closest competitor. • Delivers data management. • Provides comprehensive & integrated analytics. • Make streaming machine data and data stored in Hadoop/NoSQL accessible, usable and valuable across the organization. Value proposition • Lets customers access the data they need, wherever it resides, and make it available to their analytics tools so that it can be analyzed. • Enables customers to perform analytics on ever increasing volumes and varieties of data in Hadoop. • Makes it faster and easier for “real people” to gain insights. • Provides data aggregation to powerful analytics and delivery through data visualization, helping customers derive deeper insights. • Provides customers with a single, integrated view of transactional analytics and big data workloads, enabling predictive, actionable analytics. • Delivers real time operational intelligence by enabling organizations to centrally collect, correlate, enrich, search, analyze, and visualize massive streams of real time and historical machine data. Use cases • Financial services firms assess risk and achieve compliance by combining data from different sources. • Pharmaceutical firms can combine data from multiple places to get products to market faster. • Fortune 50 financial services firm correlates multiple sets of data to detect cybersecurity attacks. • AutoTrader gains insight into consumer behavior to improve customer experience. • There is an analytics use case for every industry. SAS has software that is installed at more than 75,000 business, government and university sites globally and remains a leader in analytics in large part by listening to customers and adapting to their changing needs. • Manufacturing and Internet of Things (IoT) solutions that automatically monitor sensors, enable predictive maintenance, and integrate billing without downtime or human intervention. • Internet of Things analytics: New York Air Brake manages intertrain forces to better manage acceleration and braking. • Operational and marketing analytics: Dominos evaluates online sales data across 10,000 stores to gain business and marketing insights. Joint analytics solutions at a glance © 2014-2015 Cisco and/or its affiliates. All rights reserved. CISCO DATA VIRTUALIZATION Analytics for Driving Better Business Outcomes: February 24th, 2015 www.cisco.com/go/unlockbigdata Unlock Your Competitive Edge Webcast: October 21st, 2014 www.cisco.com/go/unlockbigdatasolutions Cisco Big Data website: www.cisco.com/go/bigdata For more information: