Big Data and Telecoms – Eleven reasons why Big Data for Telecoms is different..

 

 

 

 

 

 

 

 

I have been working on these ideas over the past few posts

In this blog,  I present eleven reasons why the idea of Big Data for Telecoms is different from conventional Big Data

These ideas are part of my forthcoming Oxford University course on Big Data and Telecoms and also my next book Mobile Data Scientist

Today, there is genuine change in the Telecoms ecosystem.

To paraphrase Dylan – the times they are a changin’ because for the first time – Telecom Operators on both sides of the Atlantic are less constrained by regulations that hampered them (as opposed to Web companies) See What happens when Telecoms Operators can profit from the Data they hold

Also, so far, the idea of Big Data has been driven by the Web ..

So, the proposition is: When it comes to Telecoms/Mobile – there are additional considerations.

Here’s why ..

1)      The Harvard business review says that the role of the Data scientist will be one of the hottest roles going forward. How will the role of Data scientist differ for the Telecoms / Mobile ecosystem?

2)      Increasingly – Telecoms / Mobile will need to have the ability to handle real time data and many ideas taken from the web will not apply to Telecoms (ex see How do IOT appstores differ from conventional appstores )

3)      IOT and Big Data is a specific subset of Telecoms –and it will  need some unique considerations – (ex Why interoperability is critical to making the Internet of Things work)

4)      The taxonomy of Telecoms data is unique. In other words, the future Telecoms network would be able to see many facets of their customer through data categories which are only now beginning to manifest. More on this in a subsequent post

5)      Further to the above point, augmenting telecoms data with social data will be a key element of Big Data going forward

6)      The assisted web will be different for Telecoms – the best example of this is ‘Google now’ for Telecoms but with physical data overlaid

7)      Big data analytics for Telecoms – will be based on classic Big Data algorithms such as predictive algorithms, machine learning algorithms etc but specific considerations for these algorithms will apply based on datasets and Telco domain knowledge

8)      Secondary uses of data sets and data clusters – many datasets will have secondary uses and will be hence potentially monetizable. For example – an analogy is – Bus routes which could be used to create a system to indicate when the next bus is due (which is a secondary use of the route dataset)

9)      Other Industries will become data enabled and that means more datasets could be merged/amalgamated to create new insights. Last week, I saw a presentation from the     Research Data Alliance which implements the technology, practice, and connections that make Data Work across barriers. The Research Data Alliance aims to accelerate and facilitate research data sharing and exchange. Such initiatives will be more common and bring new industries together providing an opportunity to leverage Telecoms data

10)   Telco APIs .. may finally find an area they could be used in!

11)   The idea of Nappies and Beer .. could have a more specific impact for Telecoms when Real time and social media data are merged with Telco data

These ideas bring together many elements from the Telco and the Web world – which exist in isolation – but can provide new value in amalgamation. The timing is right and they are already happening (AllAboard: a system for exploring mobility and optimizing transport in developing countries using cellphone data)

If you would like to be added to our mailing list on Big Data – please email me at ajit.jaokar at futuretext.com

PS – I am writing a paper on Internet of Things and Big Data at the Internet of Things Mashup day in Oxford. If you would like a copy please tweet @webinosproject and #iotmashup