Dadasaheb Landage, Senior Support Analyst at Cerillion, investigates the rise of “Big Data” and analyses what this means for the Telco sector.
Big Data is undoubtedly one of the hottest topics in the IT industry today. In general it refers to the collection, storage, transformation and analysis of massive quantities of data – essentially turning raw data into valuable information for making business decisions. And harnessing this power is seen as the key to the next stage of operational efficiency and growth for many companies.
In any organisation, decision-making becomes much more straightforward when the management team has timely access to the right information. And the information becomes even more useful when you can dynamically analyse, interpret and visualise large sets of data to identify and take advantage of new opportunities. This is the basic motivation behind the invention of “Big Data”.
What defines “Big” largely depends on the organisation and the amount of data that it’s currently dealing with. Many organisations may regard a few hundred gigabytes of data as “Big”, but for some the scale may go well into the terabytes and petabytes. And with hardware and software technologies evolving all the time it’s a rapidly moving target.
So let’s take an example from within the telecoms sector…
The digital revolution combined with the rise of smartphones and tablets is generating vast amounts of data and putting every CSP’s infrastructure at stake. Consider all the calls, messages and browsing done on every device, plus all the application usage and downloads, not to mention all the problem reports/service requests made and all the incidents/events/logs generated in their OSS/BSS for millions of subscribers.
Then take the retention rules set by the industry regulators, and translate that into the space required just to store it. Very quickly the CSPs will run out of capacity in the existing storage and management systems and without a Big Data strategy it will become nearly impossible to analyse the stored bits and bytes.
Storage is of course getting cheaper all the time, but the real challenge lies in correlating and analysing the huge volumes of both structured and unstructured data to gain any sort of meaningful insights. Is it possible to analyse this amount of data? Certainly not using traditional database management systems and business intelligence tools, and that’s where Big Data analytics comes into the picture.
Like every database management system (DBMS), Big Data analytics aims to put data to work for your organisation. But remember Big Data is not a system or technology, it’s a concept, and one which many big organisations such as IBM and Oracle are trying to realise into analytics solutions.
So how may a CSP use Big Data? Here are just three examples where clear benefits can be derived:
• Firstly, since customers are at the centre of any business, a CSP can use Big Data analytics for more proactively managing the customer experience. The traditional approach to customer management is waiting for a customer to report a problem. However with Big Data, not only can CSPs easily query near real-time data from across the business to identify the root cause of such issues, but more importantly they can also start to identify service issues before they impact their customers and learn to predict where problems will occur.
• Secondly, Big Data can be used to increase revenue by identifying up-sell and cross-sell opportunities. By combining location information, device management and applications usage, CSPs have all the assets at their disposal to create new targeted offerings as well as shoring up revenue holes where over-the-top (OTT) services now prevail. Furthermore, when equipped with the latest online charging systems, this information can also be used to offer real-time promotions that drive immediate revenue growth.
• And thirdly, there is huge potential to create brand new revenue streams by selling their Big Data intelligence to other organisations. From insurance companies and advertisers, to high street retailers and credit card companies, the opportunity to leverage the CSPs’ data for creating improved service offerings is enormous. Just take Telefónica Dynamic Insights
as one example. Privacy concerns mean that these services are typically only based on ‘anonymised’ data used to identify trends, but just imagine the power and value that could be delivered if customers would consent to their personal information being used?
CSPs already have the information in their existing systems, but it is simply too time consuming and costly to retrieve, correlate and analyse this to its full potential. Big Data brings it all together, creating new perspectives on their customers and services, and opening a wide array of growth opportunities. However, a Big Data solution on its own won’t give you all the answers. First, you need to have a good idea of what questions you want to ask of it.