 | Issue: | EMEA 2012 |
| Article no.: | 12 | |
| Topic: | Is big data the next big thing for telecom? | |
| Author: | Alon Aginsky | |
| Title: | CEO & President | |
| Organisation: | cVidya Networks | |
| PDF size: | 231KB |
About author
Alon Aginsky is CEO and president of cVidya Networks, the provider of revenue intelligence solutions for telecoms, media and entertainment service providers that he established 11 years ago. AlonAginsky founded cVidya Networks and assumed its lead role 10 years ago, bringing with him over 20 years of management and marketing experience in the telecommunications, software development and network management industries.
Prior to cVidya, Mr Aginsky served as Vice President of Business Development and Business Alliances at C. Mer Industries, where he was responsible for new ventures in Telco customer care, billing, and network-management solutions. He was also Vice President of Sales and Marketing at Mer Tele-management Solutions, where he was responsible for the company’s global marketing and sales efforts. In this capacity, Mr Aginsky successfully led the public offering of MTS on NASDAQ. A born entrepreneur, he also helps young startups grow and prosper.
Alon Aginsky holds a BA in Business Administration from New York Technology University.
Article abstract
The communications industry was made for ‘Big Data’ – managing vast volumes in real-time. Big Data is characterized by three V’s: Volumes (demand for voluminous data), Variety (new types, varied and unstructured, from new sources), and Velocity (rapidly analysed, through distributed processing). Big Data needs big BI (Business Intelligence) and analytics, such as the open source Hadoopand MapReduce. This can determine anything from personalized offerings to detected fraud. To capitalise on Big Data, mobile carriers must co-operate withOTTSocial Media and in turn, help these Internet players monetise the applications.
Full Article
As the volume of data in the digital universe grows to 2.7 zettabytes, IDC estimates that Big Data will earn its place as the next ’must have’ competency. In this article, we will review what Big Data is, what all the hype is about and whether or not it is justified. We will examine some of the key opportunities for CSPs (Communications Service Providers) to monetize Big Data, as well as the challenges they will face. Finally, we will determine if Big Data is really the “next big thing” for Telecoms and what you should be doing in order to be a part of it.
CSPs regularly handle billions of transactions and petabytes of data and they have been doing it for years. So, what has changed and how is the Big Data phenomenon different? According to Gartner, Big Data is becoming a metaphor for:
1. Increasing volumes of information
2. Finding information in previously ignored or new data types
3. Hadoop and MapReduce
Let’s delve into each of these assertions. ’Increasing volumes of information‘ refers to the explosion of digital content, which according to IDC will grow 44 times this decade alone, reaching a whopping 35.2 zettabytes. That’s 35.2 trillion gigabytes, or 35.2 billion terabytes or simply 35,200,000,000,000,000,000,000. As mind boggling as these numbers are, they tell only part of the story. The most striking thing about this figure is that by the end of this year, over 80 per cent of this information will be unstructured or semi structured. This leads us into the second assertion, which is that this data is coming from new or previously ignored data sources and types, such as log files, clickstreams, social networks, text, images, audio, RFID sensors reads, location information from mobile devices and geospatial images. These data sources and types are increasing at a much faster rate than traditional or “structured” data types and are full of rich information that is challenging to analyze and monetize.
The final assertion, Hadoop and MapReduce, refers to the technologies that are needed to store, manage and analyse Big Data cost effectively. These are not the SQL, or relational databases that we use for internal data or transactional data stored in traditional data warehouses and processed in our ERP, CRM or Billing systems. Hadoop is a collection of open-source, distributed fault tolerant data-processing components for storing and managing large volumes of structured, unstructured, or semi structured data. It enables applications to work with thousands of nodes and petabytes of data. Hadoop runs on low-cost commodity hardware and it scales up into the petabyte range at a fraction of the cost of commercial SQL based storage and data-processing alternatives. As Big Data platforms such as Hadoop are becoming mainstream, the potential for monetizing this tidal wave of new data is enormous.
It’s no wonder then that IDC estimates that in 2012, Big Data will earn its place as the next must-have competency. According to Mckinsey, Big Data is identified as the “The next frontier for innovation, competition, and productivity” and Accel, the venture capital firm behind Facebook and Groupon, has recently created a US$100M fund dedicated to dealing with Big Data.
Another way of recognizing Big Data is to apply the threeVs, namely Volume, Variety (multi-structured data) and Velocity (incoming data needs quick analysis and decision making). Big Data is often defined as data that has at least two characteristics out of the three Vs.
Now that we understand what Big Data is and what the hype is all about, let’s examine its implications to the communications industry. Could it also be the “next big thing” for Telecoms? In many ways, CSPs are ideally positioned to leverage the Big Data opportunity. They have been dealing with continually growing sets of data for years, regularly handling billions of transactions and monitoring and analysing petabytes of data. In addition, the Big Data growth is driven primarily by data that is consumed or generated by the Telco’s mobile customers via their mobile devices and mobile apps, be it feature phones, smartphones or tablets, all over the Telco’s network:
– In 2011 global mobile data traffic was over eight times greater than the total global Internet traffic in 2000.
– More than 50 per cent of Facebook users are mobile users, a staggering 488 million mobile users.
– According to Gartner, in 2011 1.8 billion mobile phones were sold, of which 31 per cent were smartphones.
– According to the Cisco VNI Mobile Traffic Forecast, in 2011 the typical smartphone generated 35 times more mobile data traffic (150 MB per month) than the typical basic-feature cell phone.
– Not only is the smartphone market share growing, but also the usage of typical smartphones has increased threefold since 2010.
To a large extent, it seems as if the communications industry was made for Big Data. In today’s ever-changing, highly competitive and complex environments, Telecoms need BI (Business Intelligence)& Analytics to play a pivotal role in helping them to increase ARPU, reduce churn and drive growth and profits. Let us examine how Big Data analytics can help CSPs capitalize on the Big Data wave:
– Powering Telecom BI & Analytics: The most obvious opportunity for CSPs in Big Data is to add Big Data technologies and capabilities to their BI and Analytics. This will enable them to process and correlate new data sources and types with traditional ones, to achieve better, more efficient results and insights. Pricing analytics and Next Best Offer recommendation apps in particular, are classic examples. By analysing structured data (such as actual subscriber usage) and unstructured or semi-structured data types (such as log files, clickstreams and text from e-mails), CSPs can provide more accurate and personalized offer recommendations. The recommendation engine can match price plans and add-ons based also on customer preferences and behaviour, such as sport add-ons for sport fans and free audio book offers for commuters. This helps CSPs decrease the retention costs of existing subscribers as well as identify up-sell and cross-sell opportunities to help drive ARPU and reduce churn. Another example is for fraud management application: by adding Big Data capabilities and data sources and correlating them with traditional data sources, CSPs can optimize the detection of fraudsters as well improve the efficiency and accuracy of recognizing patterns or anomalies of fraudulent activities.
– Cooperate with social network players in monetizing big data: While social network players have mostly figured out their monetization strategy at the desktop, it is not that clear for mobile devices. This fact was recently highlighted by Facebook during their IPO filing. They described the growing use of mobile devices as a risk, as they did not realize meaningful revenue streams from the use of their mobile products. This presents a huge opportunity for CSPs to partner with these players and find a win-win solution for monetizing big data via the mobile channel.
– Data markets: CSPs are positioned at the core of the Big Data explosion and should leverage this to their advantage by taking advantage of the opportunity to sell and monetize this data directly by either creating their own data marketplaces or via 3rd parties. However, CSPs must ensure that they do that while carefully addressing the privacy and legal aspects of sharing this data. Examples of such strategies can be seen in Microsoft’s Azure Data Marketplace, the UK based startupDataSift and the recent Big Data initiative by the White House which made 200 terabytes of data from the “1000 Genomes Project” available on Amazon’s cloud.
– Democratizing Big Data: Providing small and medium businesses (SMBs) with Big Data insights and tools over the cloud to allow them to benefit from Big Data at a fraction of the cost. This saves SMBs the hassle and cost of installing hardware and software, sourcing expertise required for managing Hadoop clusters and the need to employ data scientists and analysts to mine them. Examples of this approach can be seen in the Intuit Small Business Index (sharing Big Data insights with the ’little guy‘), with Jigsaw Data.com which is a Salesforce.com crowd-sourcing platform for contacts, and Google’s recent Big Query launch of cloud-based analytics services designed to speed up data analysis and sidestep the big-data skills gap.
Indeed, there are plenty of big opportunities for CSPs when it comes to Big Data. As such,it is highly likely that it will become the next-big-thing for Telecoms. However, in order to reap the full benefits of Big Data, CSPs will need to overcome considerable challenges. They will need to adopt new technologies and architectures needed to process Big Data. They will also have to address the limited talent pool of data scientists and analysts required to mine Big Data. In addition, they will need to address the privacy and legal aspects of Big Data in order to remain competitive in an era where information is the new currency, while ensuring that they remain a trusted brand in the eyes of their customers as well as taking into account the differences between Europe and the US. For example, by adhering to policies such as opt-in instead of opt-out, providing clear and fixed privacy policies and committing to erase personal data after X years.
Last but not least is the issue of timing. While CSPs are well positioned to capitalize on Big Data they are lagging behind social networks and over-the-top players such as Google, Facebook and Amazon who entered the game earlier. To overcome this challenge, CSPs need to act quickly and decisively, partnering with key players across the ecosystem to help them capitalize on the Big Data opportunity swiftly and efficiently. The time to act is now!
