Cisco India Blog

The role of the network in Analytics

December 13, 2016

In my previous blogs, we discussed the role of the network in securing the enterprise and IoT. This time, the focus will shift to the role that the network plays in analytics.

Analytics has played a key role in the business success of many enterprises. Analytics helps them in understanding their customer needs much better and adapting their services and products accordingly. It also helps in reducing the risks associated in rolling out new products. The infrastructure for analytics have been built so far based on use cases in the consumer space, and therefore, the role that the network has played so far is fairly limited. However, this landscape is changing rapidly, and there are several scenarios that warrant the network to play a role in analytics. The network has a lot of data that can be leveraged for analytics and thereby provide significant value to customers.


Security-driven analytics: Security is one of the key areas where analytics driven by data from the network helps in detecting and mitigating threats, as well as just provide deeper visibility into the traffic. This becomes all the more important as a significant percent of the traffic is encrypted end-to-end, thereby making it difficult for the network to provide the level of visibility and security that customers would like to have. The data from the network elements (switches, routers and access-points) helps provide information about network traffic that helps in security analysis. This space is primed for significant disruption in the short term, with the network playing the critical role of collecting data that is relevant and necessary for the analysis.


IoT-driven analytics: IoT is the second area where analytics will play a major role. Sensors measuring different parameters can help drive analytics which in turn can drive outcomes/decisions. The potential of sensors lies in its ability to gather data about the physical environment, which can then be analyzed or combined with other forms of data to detect patterns. As an example, the video stream from a camera can be analyzed to identify physical security events like glass break, gun shot etc. The network can then provide both prioritization for the traffic as well as alert law enforcement about the event which leads to emergency response. Securing IoT devices is another aspect that can leverage analytics to a large degree. All of this requires the network to play a critical role in running the analytics on the box that would help reduce/eliminate the latency that would otherwise be experienced if the analytics were to run in the cloud.


Business-driven analytics: The network has data that can be leveraged to drive business decisions as well. As an example, the location information derived from WiFi-based triangulation of customer-owned handhelds in a retail will help business owners make better decisions on the positioning of the various departments in the store. There are more features in the network that can be leveraged for driving such business decisions.


IT-driven analytics: IT administrators/managers can leverage analytics to help solve some of the common problems that they will need to address. The network will provide the data required to help them make better decisions.


  • Capacity planning is one of the key decisions that has to be made by IT managers today. Analytics based on the traffic profile will help them make better decisions about when (and where in the network) they would have to increase their network capacity.
  • Optimizing the network design based on traffic profiles – it’s likely that there are some buildings in the campus that have users that generate more traffic than the rest, and therefore plan the capacity accordingly.
  • Analyzing the application profile that transits the enterprise network – this would help identify the right policies that need to be enabled to achieve increased productivity.
  • Analytics of failure logs that can help in predicting future failures, that would help IT admins deign a contingency plan.


In summary, we’re only starting to scratch the surface in terms of the role that analytics can potentially play in the networking space. There will be newer use cases that will come up soon where analytics will help move the needle significantly for customers. There is, indeed, no better time to combine the power of networking and analytics to enable customer success.

Leave a comment


  1. Broad summary of analytics. But lacks concrete use cases.

    1. Two or three actual problems in security, IOT need to be explained in detail.
    2. How are we solving these problems with existing mechanisms and whether these mechanisms are adequate and efficient ?
    3. If current mechanisms are not efficient then we may just need to make them efficient
    4. If the existing mechanisms are not adequate then we can evaluate how analytics can help.
    5. If analytics is needed what is the complexity of software changes needed, overhead of analytics, how to interface with analytics engine, how to integrate analytics result with the management/orchestrator

  2. Doubt on “Security-driven analytics”. If the packet is encrypted end-to-end, then what role can network play as it anyway cannot look into the packet. This is something which I am curious about.

    Also one more Analytics which we submitted for the innovation award was “Code Flow Analytics”. Basically, we track how the code flow callgraph happens in the system to design and manage our code better. Idea was basically, if we can think of 400G worth of data in the network going through analytics, we can definitely do analytics of our software code too for better quality code.