We made it…another successful Strata-Hadoop World show for Cisco’s Big Data & Analytics team. This year we had a few unique challenges – the Pope was leaving town when we arrived; then the UN General Assembly made traffic a bit more difficult than normal; finally towards week’s end the threat of ‘The Hurricane’ for the East Coast…
Cisco had an active presence at Strata this year with several newsworthy and interesting highlights:
• Introducing Cisco Data Preparation. Cisco Data Preparation (Data Prep) makes it easy for non-technical business analysts to gather, explore, cleanse, combine and enrich the data that fuels analytics. Read Kevin Ott’s Data Prep blog here. Read More »
Tags: Big Data, Cisco, Cisco Data Preparation, Cisco Data virtualization, Cisco UCS, Cloudera, Hortonworks, IBM, IBM BigInsights, Integrated infrastructure, Intel, MapR, nexus, Splunk, Splunk Enterprise, versastack
Delivering on the promise of Big Data and Analytics takes an ecosystem of partners who collaborate to integrate the underlying technologies so your organization can turn data into business value – faster. That’s why Cisco and MapR are teaming to deliver integrated solutions that are transforming the way organizations deploy and capitalize on the value of Hadoop technology.
The Cisco UCS Integrated Infrastructure for Big Data with MapR solution combines the MapR Distribution including Apache Hadoop with Cisco UCS Integrated Infrastructure for Big Data, which unifies computing, storage, connectivity, and management capabilities. This validated solution delivers an industry-leading architectural platform for Hadoop-based applications.
Cisco and MapR continue to innovate to enable new customer use cases. MapR Senior Solutions Architect, Dr. James Sun, provides an excellent example on his latest blog on Dockerizing Apache Webservers with Cisco UCS, Apache Mesos and MapR.
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Tags: Big Data, Hadoop, MapR, Strata Hadoop, UCS
Next in our series of Why I Love Big Data is Bruce from MapR. Together, Cisco and MapR are working on a very cool solution for keeping data local, but accessing very quickly. Also, come by the Connected Banking stand in the Cisco Live World of Solutions and DevNet area to see a demo of the distributed system. You will see how Cisco and MapR can provide solutions for security and data theft prevention to prevent theft of customer’s personal data and financial information.
Bruce Penn, Principal Solution Architect, MapR Technologies
Bruce is a Principal Solution Architect with MapR Technologies. He has over 22 years of Information Technology experience that includes Data Warehousing, Business Intelligence, Enterprise Architecture, Systems Design, Project Management and Application Programming. Prior to MapR, Bruce spent 8.5 years at Oracle and was instrumental in helping grow the Oracle Exadata Database Machine business through extensive collaboration with several large enterprise customers. Bruce was the first Solution Architect to join MapR’s Sales Engineering team and has been solely focused on the MapR Distribution for Hadoop and associated Apache Hadoop ecosystem technologies ever since. Bruce holds a Bachelor’s Degree in Electrical Engineering from Michigan State University.
Cisco and MapR have long been partners in the big data market, and with enterprises embracing the Internet of Everything (IoE) and moving towards a truly distributed data center environment, the combination of UCS and MapR provide unique capabilities to simplify this architecture.
Cisco UCS servers provide a powerful foundation for running distributed big data/Hadoop MapR clusters with unparalleled performance, availability, and manageability at the hardware level. The MapR Distribution including Apache Hadoop provides similar robustness at the software level, creating a rock-solid distributed platform for many flavors of IoE applications.
With the advent of IoE applications, data often originates at the “edge” of a system’s network, meaning that devices such as routers and switches in one data center will generate log data locally, while devices in other data centers will do the same creating silos of log data. In order for applications built around this log data to react in real time, they need to access that data as quickly as possible, and often those applications will want to aggregate the data across data centers in order to make decisions quickly, while keeping the data local to the originating data center. It may be important to keep the data local for legal and regulatory reasons, as well as for efficient local queries. With Cisco UCS Servers, MapR Data Placement Control, and Apache Drill, this becomes a simple task.
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Tags: analytics, BigData, Cisco, CiscoUCS, MapR, SQL, WhyILoveBigData
Why do I love Big Data so much? It’s because there are endless possibilities to deliver on the Internet of Everything (IoE) opportunity that will create new capabilities, richer experiences, and unprecedented economic opportunities for businesses, countries, and individuals. Analytics is an enormous part of that value creation and is estimated to drive $7.3T of the $19T IoE opportunity over the next 10 years.
Big Data and Analytics take the data created by people, processes, and things – that’s held within the Data Center and at the Edge – and convert it to insights that deliver the truly transformational business outcomes for which we all strive. I’m not talking about ‘iterative’ changes here. I’m talking about game-changing breakthroughs that change the way businesses compete, healthcare teams treat their patients, and cities and governments meet the needs of their constituents.
Cisco has incredible Connected Analytics offerings that address the needs of data streaming at the edge. These offerings are complemented by solutions based on Cisco UCS Integrated Infrastructure and broad ecosystem of Big Data & Analytics Partners.
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Tags: #CLUS, BigData, cisco live, Cisco UCS, CiscoUCS, Cloudera, ConnectedAnalytics, Hortonworks, MapR, Platfora, SAP, Splunk, Tableau, ucsbigdata
Hadoop is a Game Changer ! Cisco and MapR have partnered to offer a comprehensive portfolio for enterprise Hadoop deployments that combines Cisco UCS and the MapR Distribution for Apache Hadoop. With significant investments in architectural innovations, the joint solution offers a high-performance platform that can be optimized and scaled for any size to meet the demanding needs of our customers. Today, we are announcing the 3rd generation of our joint solution:
- Based on Cisco UCS Integrated Infrastructure for Big Data – extending our vision of Integrated Infrastructure to help organizations deploy and scale applications faster to drive the revenue side of the business, while reducing risks and TCO
- Taking full advantage of the high performance compute, internal storage and active-active network fabric with crucial investments in MapR improving performance and scalability while maintaining the Apache Hadoop API and application compatibility for broad applicability
- Large scale production deployments in a range of industries including finance, healthcare, media retail and government
- Foundation for an enterprise data hub with support for out-of-the-box multi-tenancy ensuring application level SLAs, guarantee isolation, enforce quotas, job placement control, security and delegation as well as providing a low cost of operations and simpler manageability with UCS Manager and the MapR control system
- Fully automated provisioning and deployment of a cluster with Cisco UCS Director Express for MapR with a single management pane across both physical infrastructure and Hadoop software, with advanced application-level monitoring
- Scalability to very larger clusters with Cisco Application Centric Infrastructure, enabling multi-tenancy, policy-based flowlet switching, packet prioritization to deliver- throughput on demand, leading-edge load balancing across UCS domains.
Solution Brief: Cisco UCS Integrated Infrastructure for Big Data with MapR
Cisco Validated Design: Cisco UCS Integrated Infrastructure for Big Data with MapR with Multi-Tenancy Extension
Cisco UCS Big Data Design Zone
Cisco UCS Solution Accelerator Paks for Big Data
Tags: Big Data, Hadoop, MapR, Multi-Tenancy