The phenomenal growth of data today requires that service providers not only understand big data to decipher the information that counts, but also -- more importantly -- the possibilities of what they can do with it using big data analytics.
Service providers are sitting on terabytes of data that are stored in silos and scattered across the organization. In order to exploit the full potential of this stored data, service providers must have solutions that can help them correlate, process, and decipher nuggets of actionable information.
This is not possible without big data and advanced analytics. For simpler and faster processing of only relevant data, service providers need an advanced analytics-driven big data solution that will help them to achieve timely and accurate insights using data mining and predictive analytics, text mining, forecasting, and optimization capability to continuously drive innovation and help service providers make the best possible decisions.
Operators face an uphill challenge when they need to deliver new, compelling, revenue-generating services without overloading their networks and keeping their running costs under control. The market demands a new set of data management and analysis capabilities that can help service providers make accurate decisions by taking into account customer, network context, and other critical aspects of their businesses. Most of these decisions must be made in real time, placing additional pressure on the operators. Real-time predictive analytics can help leverage the data that resides in their plethora of systems, make it immediately accessible and help correlate that data to generate insight that can help them drive their businesses forward.
Heavy Reading defines big data and advanced analytics as the utilization of hardware and software solutions designed to process large volumes of data (in the range of hundreds of terabytes) to unearth actionable insight. Big data is a combination of both structured and unstructured data coming from text, social media, video, etc. As such, real-time streaming technology and complex event processing technologies are part and parcel of big data solutions.
Heavy Reading expects the big data technology and services market (for the communications service provider sector) to grow from $1.95 billion in 2013 to $9.83 billion in 2020. This represents a total compound annual growth rate (CAGR) of 26%. Breakout CAGR growth between software, hardware and services are: software will grow at 29.3% CAGR; hardware will grow at 22.8% CAGR; and services will grow at 26.8% CAGR.
North America continues to be the biggest spender on big data and advanced analytics. We expect spending in this region to grow from $936 million in 2013 to $4.37 billion in 2020 (24.6% CAGR). EMEA is next, with a spending of $565.5 million in 2013, estimated to grow to $2.97 billion in 2020 (28 percent CAGR). Asia-Pacific follows with $292.5 million in 2013, growing to $1.6 billion in 2020 (26.8% CAGR). Central/Latin America accounted for $156 million in 2013, which will grow to $874.7 million in 2020 (27.9% CAGR).
Our research on big data and advanced analytics -- based on operator interviews, surveys, etc. -- has unearthed some very interesting points. Some of them are highlighted below:
- The majority of communications service providers across the globe believe that real-time analytics is important to their success and is a critical component of their big data strategy.
- "Inability to integrate disparate systems and data" and "regulatory concerns" are identified as the top two reasons preventing operators from adopting products and services for big data initiatives. Security concerns and privacy concerns come very close as well.
- The majority of operators we have interviewed believe that their big data initiative will be fully implemented by 2015.
- The majority of service providers from all regions predict that it will take one to two years for their company to see increased revenue from its big data and analytics initiatives.
- Regulatory concerns and the inability to integrate disparate systems of data are the key factors that most service providers feel are preventing their company from adopting products or services for big data initiatives.
- The quality of data along with business case justification are the biggest challenges that service providers face when trying to implement real-time data analytics use cases.
- Targeted offer and campaign management, churn prediction and proactive customer care are the top three pain points that operators believe can be resolved by big data and advanced analytics in the next 12-24 months.
Big data and advanced analytics is a major research focus for Heavy Reading. Please look for more reports, market sizing and other information on this topic on the Heavy Reading SPIT Total Access portal.
— Ari Banerjee, Senior Analyst, Heavy Reading