Big Data is not just about gathering tons of data, the digital exhaust from the internet, social media, and customer records. The real value is in being able to analyze the data to gain a desired business outcome.
Those of us who follow the Big Data market closely never lack for something new to talk about. There is always a story about how a business is using Big Data in a different way or about some new breakthrough that has been achieved in the expansive big data ecosystem. The good news for all of us is, we have clearly only scratched the surface of the Big Data opportunity!
With the increasing momentum of the Internet of Everything (IoE) market transition, there will be 50 billion devices connected to the Internet by 2020—just five years from now. As billions of new people, processes, and things become connected, each connection will become a source of potentially powerful data to businesses and the public sector. Organizations who can unlock the intelligence in this data can create new sources of competitive advantage, not just from more data but from better access to better data.
What we haven’t heard about – yet—are examples of enterprises that are applying the power of this data pervasively in their organizations: giving them a competitive edge in marketing, supply chain, manufacturing, human resources, customer support, and many more departments. The enterprise that can apply the power of Big Data throughout their organization can create multiple and simultaneous sources of ongoing innovation—each one a constantly renewable or perpetual competitive edge. Looking forward, the companies that can accomplish this will be the ones setting the pace for the competition to follow.
Cisco has been working on making this vision of pervasive use of Big Data within enterprises a reality. We’d like to share this vision with you in an upcoming blog series and executive Webcast entitled, ‘Unlock Your Competitive Edge with Cisco Big Data Solutions’, that will air on October 21st at 9:00 AM PT.
I have the honor of kicking off the multi-part blog series today. Each blog will focus on a specific Cisco solution our customers can utilize to unlock the power of their big data – enterprise-wide– to deliver a competitive edge to our customers. I’m going to start the discussion by highlighting the infrastructure implications for Big Data in the internet of Everything (IoE) era and focus on Cisco Unified Computing System initially.
Enterprises who want to make strategic use of data throughout their organizations will need to take advantage of the power of all types of data. As IoE increasingly takes root, organizations will be able to access data from virtually anywhere in their value chain. No longer restricted to small sets of structured, historical data, they’ll have more comprehensive and even real-time data including video surveillance information, social media output, and sensor data that allow them to monitor behavior, performance, and preferences. These are just a few examples, but they underscore the fact that not all data is created equally. Real-time data coming in from a sensor may only be valuable for minutes, or even seconds – so it is critical to be able to act on that intelligence as quickly as possible. From an infrastructure standpoint, that means enterprises must be able to connect the computing resource as closely as possible to the many sources and users of data. At the same time, historical data will also continue to be critical to Big Data analytics.
Cisco encourages our customers to take a long-term view—and select a Big Data infrastructure that is distributed, and designed for high scalability, management automation, outstanding performance, low TCO, and the comprehensive, security approach needed for the IoE era. And that infrastructure must be open—because there is tremendous innovation going on in this industry, and enterprises will want to be able to take full advantage of it.
One of the foundational elements of our Big Data infrastructure is the Cisco Unified Computing System (UCS). UCS integrated infrastructure uniquely combines server, network and storage access and has recently claimed the #1, x86 blade server market share position in the Americas. It’s this same innovation that propelled us to the leading blade market share position that we are directly applying to Big Data workloads. With its highly efficient infrastructure, UCS lets enterprises manage up to 10,000 UCS servers as if they were a single pool of resources, so they can support the largest data clusters.
Because enterprises will ultimately need to be able to capture intelligence from both data at rest in the data center and data at the edge of the network, Cisco’s broad portfolio of UCS systems gives our customers the flexibility to process data where it makes the most sense. For instance, our UCS 240 rack system has been extremely popular for Hadoop-based Big Data deployments at the data center core. And Cisco’s recently introduced UCS Mini is designed to process data at the edge of the network.
Because the entire UCS portfolio utilizes the same unified architecture, enterprises can choose the right compute configuration for the workload, with the advantage of being able to use the same powerful management and orchestration tools to speed deployment, maximize availability, and significantly lower your operating expenses. Being able to leverage UCS Manager and Service Profiles, Unified Fabric and SingleConnect Technology, our Virtual interface card technology, and industry leading performance really set Cisco apart from our competition.
So, please consider this just an introduction to the first component of Cisco’s “bigger”, big data story. To hear more, please make plans to attend our upcoming webcast entitled, ‘Unlock Your Competitive Edge With Cisco Big Data Solutions’ on October 21st.
Every Tuesday and Thursday from now until October 21st, we’ll post another blog in the series to provide you with additional details of Cisco’s full line of products, solutions and services.
View additional blogs in the series:
9/25: Unlock Big Data with Breakthroughs in Management Automation
9/30: Turbocharging New Hadoop Workloads with Application Centric Infrastructure
10/2: Enable Automated Big Data Workloads with Cisco Tidal Enterprise Scheduler
10/7: To Succeed with Big Data, Enterprises Must Drop an IT-Centric Mindset: Securing IoT Networks Requires New Thinking
10/9: Aligning Solutions to meet our Customers’ Data Challenges
10/14: Analytics for an IoE World
Please let me know if you have any comments or questions, or via Twitter at @CicconeScott.
Tags: ACI, analytics, Big Data, blade server, Blade Servers, Cisco UCS, Cisco UCS C240 M3 Rack Server, Cisco Unified Computing System, Cisco Unified Data Center, Cisco Unified Fabric, Cloudera, data virtualization, Hadoop, Hortonworks, Internet of Everything, IoE, MapR, rack server, security, UCS Central, UCS service profiles
Big Data remains one of the hottest topics in the industry due to the actual dollar value that businesses are deriving from making sense from tons of structured and unstructured data. Virtually every field is leveraging a data-driven strategy as people, process, data and things are increasing being connected (Internet of Everything). New tools and techniques are being developed that can mine vast stores of data to inform decision making in ways that were previously unimagined. The fact that we can derive more knowledge by joining related information and recognizing correlations can inform and enrich numerous aspects of every day life. There’s a good reason why Big Data is so hot!
This year at Hadoop Summit, Cisco invites you to learn how to unlock the value of Big Data. Unprecedented data creation opens the door to responsive applications and emerging analytics techniques and businesses need a better way to analyze data. Cisco will be showcasing Infrastructure Innovations from both Cisco Unified Computing System (UCS) and Cisco Applications Centric Infrastructure (ACI). Cisco’s solution for deploying big data applications can help customers make informed decisions, act quickly, and achieve better business outcomes.
Cisco is partnering with leading software providers to offer a comprehensive infrastructure and management solution, based on Cisco UCS, to support our customers’ big data initiatives. Taking advantage of Cisco UCS’s Fabric based infrastructure, Cisco can apply significant advantage to big data workloads.
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Tags: ACI, Big Data, blade server, Blade Servers, Cisco UCS, Cisco UCS C240 M3 Rack Server, Cisco Unified Computing System, Cisco Unified Data Center, Cisco Unified Fabric, Cloudera, Hadoop, Hortonworks, MapR, rack server, UCS Central, UCS service profiles
The Cloudera Sessions Roadshow helps companies to navigate the Big Data journey. As Hadoop takes the data management market by storm, organizations are evolving the role it plays in the modern data center. This disruptive technology is quickly transforming an industry, the value it adds to the modern data center, and how you can leverage it today. When combined with Cisco Unified Computing System™ (Cisco UCS®), the joint solution helps you exploit the valuable insights contained in your data to drive meaningful change in your business.
The Cloudera Sessions roadshow is designed to help organizations to identify where they are on their Big Data journey and to navigate how to stay the course in a low-risk, productive way. The Cloudera Sessions’ attendees will benefit from hearing about Cloudera and its partners’ experiences with real-world deployments, as well as those of Hadoop users who plan and manage them.
Cisco is partnering with Cloudera to offer a comprehensive infrastructure and management solution, based on the Cisco Unified Computing System (UCS), to support our customers big data initiatives. As a proud sponsor for this event, I would encourage you to join us at one of the following scheduled stops to learn more about our joint solutions for big data:
San Francisco on June 4, 2014 (Registration Link Available Soon)
New York on June 18, 2014 (Registration Link Available Soon)
More Cities to be added
Tags: Big Data, Blade Servers, Cisco UCS, Cisco Unified Computing System, Cloudera, Cloudera Sessions, Hadoop, Rack Servers, UCS
Huge amounts of information are flooding companies every second, which has led to an increased focus on big data and the ability to capture and analyze this sea of information. Enterprises are turning to big data and Apache Hadoop in order to improve business performance and provide a competitive advantage. But to unlock business value from data quickly, easily and cost-effectively, organizations need to find and deploy a truly reliable Hadoop infrastructure that can perform, scale, and be used safely for mission-critical applications.
As more and more Hadoop projects are being deployed to provide actionable results in real-time or near real-time, low latency has become a key factor that influences a company’s Hadoop distribution choice. Thus, performance and scalability should be evaluated closely before choosing a particular Hadoop solution.
The raw performance of a Hadoop platform is critical; it refers to how quickly the platform can ingest, process and analyze information. The MapR Distribution for Hadoop in particular provides world-record performance for MapReduce operations on Hadoop. Its advanced architecture harnesses distributed metadata with an optimized shuffle process, delivering consistent high performance.
The graph below compares the MapR M7 Edition with another Hadoop distribution, and it vividly illustrates the vast difference in latency and performance between these Hadoop distributions.
One particular solution that is optimized for performance is Cisco UCS with MapR. MapR on the Cisco Unified Computing System™ (Cisco UCS®) is a powerful, production-ready Hadoop solution that increases business and IT agility, supports mission-critical workloads, reduces total cost of ownership (TCO), and delivers exceptional return on investment (ROI) at scale.
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Tags: Big Data, blade server, Blade Servers, Cisco UCS, Cisco UCS C240 M3 Rack Server, Cisco Unified Computing System, Cisco Unified Data Center, Cisco Unified Fabric, Hadoop, MapR, rack server, UCS Central, UCS service profiles
This week we’re announcing new systems at the upper end of the UCS server product line: some heavy-duty iron for heavy-duty times. These are important new tools for our UCS customers: the digital age is accelerating, IT needs more horsepower to keep up, and there is a lot at stake.
Consider this: less than 10 years ago, some of the largest mainframes scaled up to half a terabyte (TB) of main memory. What if I were to tell you that these latest generation UCS blade servers will scale to 3TB? Sound like a lot? It is. And that’s just the two-processor version. Connect two UCS B260 M4 blades with an expansion connector and they become a UCS B460 M4, a four socket server that will scale to 6TB. Putting that into perspective: a spiffy new laptop might ship today with 8GB of memory. Multiply that by 750 and you have 6TB.
Not too long ago, all the content Wikipedia would fit in this type of footprint (in 2010 it was just under 6TB with media.) Here is a fun illustration of what this scale of data would look like on paper (just the ~10GB of text, not the images.) Now remember, we’re not talking about fitting all that data on the local disks of the server – we’re talking about fitting it in main memory. This is becoming crucially important in the field of data analytics, where “in-memory” is the key to speed and competitiveness. Applications like SAP HANA are at the forefront of this trend. Today, at Intel’s launch event in San Francisco, Dan Morales (Vice President of Enabling Functions at eBay) joined us to talk about how they’re betting on this type of analytic technology to help them make the eBay Marketplace work better for buyers and sellers (and eBay shareholders.) I’ll post a video clip of that soon; his description of the challenges and opportunities, at eBay scale, is worth a watch.
We’ve talked about memory scaling, and Bruno Messina has a nice post that talks more about the scalability on these systems and UCS at large. But dominating performance is the name of the game: behemoth processing performance is what we look for at this end of the server spectrum and Intel has not disappointed on this round of new technology. The next generation of the Intel Xeon E7 family packs up to 15 cores per processor and delivers an average 2x performance increase compared to previous generation products. Performance will be even higher on specific workloads, for example up to 3X on database and even higher for virtualization. Cisco’s implementation of this technology has once again set the standard for system performance. In today’s launch, Intel cited Cisco with 6 industry-leading results on key workloads. As of this posting, the closest to come to that achievement that was Dell with 4. HP ProLiant posted 1. So hats off, once again, to the engineering team in Cisco’s Computing Systems Product Group. Girish Kulkarni has a great summary of the performance news here.
Our collaboration with Intel is one of the best technology combinations in the industry today. Consider what we both bring to the party. Intel: innovation in processor technology that drives Moore’s Law. Cisco: innovation in connecting things across the data center and around the world. UCS is an outcome of two blue-chip tech powerhouses investing in real innovation and the results have changed the industry.
In 1991, Stewart Alsop famously wrote: “I predict that the last mainframe will be unplugged on 15 March 1996.” He just as famously had to eat his words. He munched on those twelve years ago, and while mainframes and RISC-based systems remain, there is an inexorable trend as the heaviest analytic workloads continue to shift to the type of scale-up x86-based systems we’re talking about today. It only makes sense. So while this will garner me plenty of comments from the architectural purists out there, I say “go ahead and plug a mainframe back in.” It will fit right in your UCS B-Series blade chassis…
Tags: Big Data, Blade Servers, Cisco Data Center, Cisco Data Center strategy, Cisco Servers, Cisco UCS, Cisco Unified Computing System, SAP. HANA, unified computing