What’s your winning combo for big data and analytics? This may come as a surprise to you – but given that the Superbowl is approaching – I am going to use a football analogy. As we get ready for the game in 2 weeks, we have a tale of two quarterbacks. One is an established quarter back with a long-standing history of victories. The other –new, up and coming—brings a ton of enthusiasm and fresh legs to the game.
This is like the analytics market place of today. We have established players like SAP, SAS, and IBM and new ones such as Splunk, Platfora, and ParStream (now part of Cisco). On this 10th birthday of Hadoop, we have established technology approaches from Cloudera, Hortonworks and MapR using MapReduce being challenged by the new player to the game – Spark, which is starting to score big in the technology field. The big 3 are taking different approaches to this, which should make it fun to watch.
Ok, guess how Cisco UCS ties into all of this? The foundation under all of these players is a solid integrated infrastructure that enables the game to be played and won. And like Levi’s stadium, UCS is the state of the art infrastructure with all of the most essential bells and whistles (Yes, I’m talking about service profiles for policy execution and management and ACI for business-relevant software defined networking (SDN)). Because in football and in business, it’s important to go ALL THE WAY, you can rely on Cisco’s end-to-end solutions to make this happen.
Trying to figure out the winning combination for your team? I pulled together a ‘scouting report’ to help you put together your ideal fantasy team. Bookmark this, because this is where you can find the latest and greatest and how each player partners with Cisco to bring you insights to action.
Cisco Big Data and Analytics Latest Content
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Tags: Big Data, CiscoUCS, Cloudera, data center, Hadoop, Hortonworks, IBM, MapR, Platfora, SAP, SAS, Splunk
Recently I was just granted the title, “Road Warrior.” If you followed me on Twitter, you probably knew that I had been traveling lots lately. And I continue to live up to that title! Next up: MapR Big Data Everywhere in Austin (10/27), Dallas (10/28), and New York (11/4)!
MapR Big Data Everywhere is a half-day conference focused on Hadoop and complementary technologies that will bring together users and developers to share their experience about thier projects. There will be multiple presentations and user success stories from which we will learn great insights .It will also be a great opportunity for Industry experts to exchange Hadoop knowledge, share best practices, and discuss Hadoop use cases.
Cisco UCS Integrated Infrastructure for Big Data and MapR continue to deliver performance and multi-tenancy to help tame big data projects. We provide enterprises with transparent, simplified data as well as management integration with an enterprise application ecosystem. Through our integration and tremendous work together, we are able to provide a uniquely capable, industry-leading architectural platform for Hadoop-based applications.
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Tags: @ciscoDC, analytics, Big Data, data center, Hadoop, MapR
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
Guest Blog by Ron Graham
Ron Graham had served as a Data Center Architect and Systems Engineer for some of the largest IT companies in the U.S. including Cisco Systems, NetApp, Sun Microsystems, and Oracle. He is currently working for Cisco Systems as a Big Data Analytics Engineer.
What is Data Virtualization? Our definition is: Agile data integration software that makes it easy to access all your data no matter where it’s managed, and query it across the network as if it were in a single place. I like to say it differently – the real value lies in its ability to provide business users with a single high-level view of data that is spread across their infrastructure.
Data Virtualization is essentially middleware software that leverages a high-performance query engine and can utilize advanced computer architectures such as Cisco UCS. It’s a virtual data integration layer that can deliver data from multiple sources that are loosely coupled or have little or no knowledge of the other components. Of course this is done in a logically organized manner as show by the diagram below.
This is all nice but where is the beef, or the sex appeal? The sexy part is in the front-end business intelligence platforms and data visualization tools that can access and analyze data such as Tableau. Tableau can simply access data through the Cisco Data Virtualization with an ODBC driver. From here, business users can query data on demand from a single point of access (i.e. a common data model) without having to understand the different schemas or SQL dialects of the original data sources.
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Tags: Big Data, Cisco, Cisco UCS, data center, Hadoop, Strata Hadoop, Tableau
Have you heard Weston Jossey explain his company’s hybrid cloud strategy before? If you haven’t, get comfortable and enjoy the recording of our most recent OpenStack Podcast. In it, Wes explains why his company chose to deploy a private cloud, what they use it for, and how they use it in conjunction with AWS to achieve maximum efficiency. Seriously–if you’re looking for tips about how to do hybrid well, this is the podcast for you. Wes makes it easy to understand both the upside and downside of private clouds in general and OpenStack-based private clouds in particular. Plus, he’s extraordinarily honest about what OpenStack is good for and what it’s not so good for. Among other things, in this interview, Wes discusses:
- Tapjoy’s big data architecture
- How they handle 5-10 billion transactions per day
- The TCO of their OpenStack-based cloud
- How he finds great hires in a competitive market
- How Tapjoy automates deployment
Have a show idea? Tweet Jeff and Niki at @openstackpod
See past episodes, subscribe, or view the upcoming schedule on the OSPod website.
To see the full transcript of this interview, click “Read more” below.
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Tags: AWS, Hadoop, Hybrid Cloud, OpenStack, podcast, Tapjoy