Big Data Transport Enters the Service Provider Vocabulary in a Monstrous Way

Glenn Hunt

Glenn Hunt

Summary Bullets:

  • Big data/analytics have arrived, to help deliver on high user and service provider expectations.
  • New database technologies and open source software form the basis for effective solutions.

Now that SDN and NFV seem to have gone from novel concept to a foregone conclusion, the telecom market’s never ending quest for the ‘next big thing’ has settled, appropriately, on big data and its counterpart big data analytics as the topic on everyone’s mind.  Okay, so maybe SDN and NFV have some time left on the hype train, but today, let’s ponder the question as to why the industry has shifted its focus from selectively collecting barely enough data to feed the billing cycle and provide SLA assurance to collecting so much data that some predict the amount of data being processed by big data analytics engines will exceed the amount of traffic on the network itself.

Several recent examples around big data and analytics include:

  • ADVA Optical Networking, Juniper Networks and the University of Michigan issued a joint announcement of a demo at SC13, which was comprised of a globally dispersed OpenFlow network, to reveal how research and education organizations can efficiently scale their networks to effectively transport multiple petabytes of data generated in scientific research collaboration.
  • Alcatel-Lucent’s Motive Big Network Analytics captures information collected by its Wireless Network Guardian (WNG) which would be analyzed by its Kindsight Security Analytics and Big Network Analytics Data Miner to provide useful insights to help operators improve application and network performance.
  • Cisco’s Network Conversion System (NCS) launch to deliver the ‘Internet of Everything’ (IoE) included Quantum Analytics as a key component of its solution.
  • Nokia Solutions Networks announced that it will utilize WANdisco’s Apache Hadoop solutions, which can store and analyze large amounts of structured and unstructured data, to deliver 100% uptime for big data storage and access across its product portfolio.

The list goes on, but this sample clearly points to a broad shift toward not only collecting vast amounts of data, but also actually using the data to meet current and future challenges.

So, why the shift now?  For years, service providers and mobile operators would have moved mountains to have a broad database of useful facts.  At the risk of oversimplifying, the answer boils down to: “Because now we can.”  OSS/BSS environments are advancing rapidly.  SDN and NFV promise to make networks smarter and more agile, and database design is becoming more elegant.

By way of example, take Ericsson’s big data announcement, which said, “The technologies that support big data are now widely available, lowering the entry barrier.”  Inherent in this release is the thesis is that innovative data base design, faster networks and the availability of open source tools are all coming together to make big data both tenable and useful.  Ericsson notes that a generation shift has occurred, moving the issues associated with big data a step higher up in the analytics chain.

It does appear that big data and big data analytics (or similar terms) will be around us for the foreseeable future.  Furthermore, it’s expected that fixed line and mobile operators will be able to leverage expanded data stores and analytical tools to address current and upcoming challenges to meet growing customer expectations, while improving their return on investment, since they will have much greater visibility into the inter-workings of their networks and very detailed knowledge of user patterns.

For better or worse, big data and big data analytics will be in our collective face for the foreseeable future.  The good news is that network operators will be presented with expanded data stores and analytical tools to make good on the new imperative to focus on customer experience rather than just network KPIs.  Of course, with big data comes big challenges.  Without a doubt, there is a big ecosystem of players trying to overcome these challenges.

Now, it’s time to see who is going to go big and who is going to go home.

About Glen Hunt
As Principal Analyst of Transport and Routing Infrastructure, Glen analyzes technology, product, and partnership initiatives of vendors who supply carrier infrastructure equipment. Specifically, focusing on vendors that produce core routers, edge switching, optical transport, data center interconnection, mobile backhaul, network management and operational support systems.

4 Responses to Big Data Transport Enters the Service Provider Vocabulary in a Monstrous Way

  1. Pingback: Big Data Exchange 23-25 March 2014 - CTOvision.com

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