Guavus CEO Anukool Lakhina discusses what telcos need to know about Big Data this year. There was movement on the Big Data front from telcos last year; what can we expect in 2013?

Anukool Lakhina: There has been a lot more investment in Big Data analytics over the past 12 months. Many operators have had that light bulb moment where they can see the potential benefits and derive business value, with a number already seeing returns.

In 2013, as confidence grows, we will see more of the same, but on a larger scale.

In particular, I think we will see telcos increasingly leverage Big Data for more networking optimisation benefits, marketing automation and monetisation, customer care, and security.

I also think many will start moving away from the traditional data warehouse “store and query” approach to data analysis, in favour of more timely insights using streaming Big Data analytics.

Many operators have already heavily invested in data warehouse solutions and analytics tools; are you saying that they should just throw these out and start again?

Not at all: Big Data tools can sit between traditional warehouses and data that flows on the network, so they can be completely complementary to traditional data warehouse and analytics tools currently in use.

However, there is a need for a new data fabric that's designed for a Big Data world, and this is where Big Data applications can help bridge the gap between new and old.

Storage is expensive, so bringing everything to the data centre to store and later query is extremely inefficient from a time and cost perspective.

Instead, by conducting streaming analytics at the edge, telcos can pan for the gold as it comes in and just send the nuggets of data back to the data warehouse to be stored and analysed more closely.

What else should operators be aware of in the Big Data space this year? 

As it stands today, Big Data analytics technology is comprised of many disparate toolsets and technologies.

What’s missing is a foundational architecture to support all these individual tools and technologies: a complete, holistic stack that can help operators get from data ingestion to data decisions in one fell swoop. 

This new architecture must recognise that a sensor-rich world creates data continuously, and in order to take immediate action, the analysis too must also be done continuously, rather than after-the-fact, once the data is stored away. 

This new architecture must also fuse a variety of data sources including internal data, data in the cloud and device data, instead of keeping them in silos. 

And it must elastically scale to the petabytes of structured and unstructured data that are now generated on a nonstop basis.

What are the most innovative ways you’re seeing network operators harness these insights?

We're seeing operators leverage Big Data to improve network capacity planning for 4G, tracking customer trends and behaviours over time to better forecast customer uptake and determine demand asking questions such as; who currently has a 4G enabled phone, where are they based, when are they due an upgrade, who are the biggest data consumers, which users were first to upgrade to 3G, and so on.

Visualising this data has enabled them to map current usage and where the biggest data consumers are currently located to aid in efficient capacity planning and determine levels of investment required to attain a good ROI during the auction process.

Another interesting area has been in creating tiered pricing structures based on actual usage.

Without timely information on consumption, many operators have been fishing in the dark in terms of data plans for customers and how to effectively price these.

Being able to identify the most profitable consumers has been a great help in not only plotting capacity, but also feeding into more targeted marketing campaigns and improving customer service and reducing customer churn.

Over time, I think operators will eventually move to a system where business processes can be triggered and automated using Big Data intelligence, using M2M communication.

What more do operators need to do to ensure they don't miss out on the opportunities Big Data presents?

The key is not to try to run before you can walk. Focus on a specific business problem that is impacting your business and work with a company that can help you to address this issue.

Many operators feel compelled to throw money at Big Data tools, as they feel they ‘should’ be doing something in this space, without really thinking about what they are looking to achieve. 

The key is to start small; identify an issue or area that could be improved by having more timely insights and work with partners that can provide a proof of concept over weeks, rather than months.

Having a use case led engagement model, as opposed to a big large blanket deployment, will be more effective and cost efficient. From there you can then look at other areas where the tool could be applied.

Want to learn more about Big Data? Click here to watch videos of our seminar; Click here to read our special report.

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