Competing with the virtual, e-commerce world is becoming increasingly challenging for real-world businesses. Traditional retailers have long envied the massive amounts of valuable data that online retailers have available to help them better understand customer behavior and implement winning marketing tactics. Online retailers know valuable information such as how frequently customers return, how long they spend on their sites, what the customers looked at but didn’t buy, and where they went before and after coming to the site. Businesses as diverse as hotels, banks, stadiums, airports, and large public venues are all looking for ways to get similar detailed data on customer activities in their facilities, so they can improve the customer experience and their bottom lines. The data and insights have not been available to bricks-and-mortar facilities, until now.
That situation is changing through the growing availability of Wi-Fi in business locations. Many retailers, hotels, and other businesses are increasingly offering Wi-Fi as a service that allows their customers to connect mobile devices to the Internet. Hidden in this valuable service is a vast amount of information and insight, which retailers and others can use to deliver tangible value to their bottom lines. Hypersensitive location information, device details, identification of returning customers, and sophisticated path analysis are just some of the customer data captured by Wi-Fi networks. Businesses are now realizing that the data and capabilities offer new ways to improve the customer experience and support a range of market-leading monetization models.
For many businesses, these new location-based experiences and Read More »
Tags: Cisco, location based services, mobile, mobile consumer survey, monetization, research, Service Provider, value-added services, wi-fi
Following part one of our Big Data in Security series on TRAC tools, I caught up with talented data scientist Mahdi Namazifar to discuss TRAC’s work with the Berkeley AMPLab Big Data stack.
Researchers at University of California, Berkeley AMPLab built this open source Berkeley Data Analytics Stack (BDAS), starting at the bottom what is Mesos?
AMPLab is looking at the big data problem from a slightly different perspective, a novel perspective that includes a number of different components. When you look at the stack at the lowest level, you see Mesos, which is a resource management tool for cluster computing. Suppose you have a cluster that you are using for running Hadoop Map Reduce jobs, MPI jobs, and multi-threaded jobs. Mesos manages the available computing resources and assigns them to different kinds of jobs running on the cluster in an efficient way. In a traditional Hadoop cluster, only one Map-Reduce job is running at any given time and that job blocks all the cluster resources. Mesos on the other hand, sits on top of a cluster and manages the resources for all the different types of computation that might be running on the cluster. Mesos is similar to Apache YARN, which is another cluster resource management tool. TRAC doesn’t currently use Mesos.
The AMPLab Statck
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Tags: AMPLab, analytics, BDAS, Big Data, BlinkDB, Cisco, custom, database, Hadoop, innovation, mapreduce, Mesos, NoSQL, Scala, security, Shark, Spark, Stack, TRAC, TRAC Big Data Analysis
If your car is overdue for a tune-up, it may let you know in unexpected (and unsettling) ways — rough handling, sluggish acceleration, and even an odd (“that can’t be good”) noise from under the hood. If you’re like me, you don’t want to find yourself waiting on the side of the road for a tow truck. You schedule your car for regular tune-ups to make sure your tires aren’t worn, the wheels are aligned, no fluids are leaking, and the engine is performing to the right specifications.
Just like your car, a collaboration infrastructure needs regular tune-ups. In fact, just like your car, a collaboration infrastructure will let you know that it’s not running optimally. But by the time you actually notice the performance problems with collaboration applications, the odds are that those problems have already started causing issues with your end-users.
Traditionally, optimization has been looked at (even by Cisco in the early days) as the final step in the deployment cycle. But IT projects queue up so fast that optimization for the last project may not happen because the next project is already underway. Today, however, we look at optimization in an Read More »
Tags: Cisco, collaboration, Collaboration Services, infrastructure, optimization, services
This week we have two opportunities for you to learn about Cisco technologies from company experts as well as our technology partners.
The first webinar, How Smarter Branches Lower Costs, is on Wednesday, December 11 at 8am Pacific and discusses how Cisco Intelligent WAN (IWAN) along with Akamai’s Unified Performance solution can help your branch offices can realistically utilize Internet as WAN for a cost-effective, reliable, and secure option.
A preview for this webinar is a quick video we did with Akamai in October!
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Tags: Akamai, Cisco, Cisco and Akamai, cmx, connected mobile experiences, IWAN, Mobility Services Enginer, mse, Webinars
Recently I had an opportunity to sit down with the talented data scientists from Cisco’s Threat Research, Analysis, and Communications (TRAC) team to discuss Big Data security challenges, tools and methodologies. The following is part one of five in this series where Jisheng Wang, John Conley, and Preetham Raghunanda share how TRAC is tackling Big Data.
Given the hype surrounding “Big Data,” what does that term actually mean?
John: First of all, because of overuse, the “Big Data” term has become almost meaningless. For us and for SIO (Security Intelligence and Operations) it means a combination of infrastructure, tools, and data sources all coming together to make it possible to have unified repositories of data that can address problems that we never thought we could solve before. It really means taking advantage of new technologies, tools, and new ways of thinking about problems.
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Tags: analytics, API, Big Data, Cisco, database, Hadoop, HDFS, innovation, Intelligence, java, mapreduce, NoSQL, operations, security, Shark, Spark, SQL, telemetry, TRAC, TRAC Big Data Analysis