The Potential of Big Data in the Telecom Infrastructure Industry

The Potential of Big Data in the Telecom Infrastructure Industry
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by Sanjeev Kapoor 12 Aug 2022

Nowadays, the amount of industrial data that is generated every year grows exponentially. This drives a transformation of many industries in a data-driven direction. The telecom industry is no exception to this trend:  Telecom companies, equipment manufacturers and telecom software solutions providers are all undergoing changes in how they do business.

The telecom infrastructure industry consists of companies that maintain the equipment used in the transmission of voice, data, text and images between countries and continents. These infrastructures also include the systems used to transmit signals across counties. The telecom infrastructure industry is therefore a heavily data-driven industry which is based on transforming vast amounts of data into actionable insights. This occurs through the implementation of advanced information technology systems that are used to improve productivity and quality assurance processes.

In recent years, the telecoms industry has experienced a revolution in data intense applications, which was driven by recent technology solutions such as machine-to-machine communications, smart services, big data and cloud computing. These technologies have become a reality in the telecommunications industry in just a few years. At the same time, the explosion of the data traffic that flows over the telecommunications infrastructures generates an increasing need to manage and optimize networks and equipment more effectively.

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Popular Data-Driven Applications for the Telecom Infrastructure Industry

There is a variety of data-driven applications in the telecoms industry. These applications leverage data generated from telecom towers, base stations and mobile networks. The processing of these data can be used for multiple purposes including effective infrastructure resource management, but also network provision and configuration.  Moreover, data driven marketing and customer focused decisions are becoming more important for the telecom operators, as well as for other companies that offer services to them.  Overall, some of the most prominent data-driven applications of the telecoms industry are:

  • Effective Infrastructure Resource Management: By using data driven analysis tools, it is possible to get a clear picture about what resources are required for which infrastructure and when they need to be provided for optimum performance. This enables effective resource management that saves costs and improves efficiency levels. The telecom infrastructure industry comprises highly complex system with multiple interdependent components that need to be managed efficiently and effectively. Big data can help manage this complexity by collecting data from all components of the system and analyzing it together. This also provides opportunities for improved decision making and resource allocation, based on the integration and analysis of many information sources from different departments such as network management, billing and customer care.
  • Data Driven Marketing and Customer Focused Decisions: Data analytics improve marketing strategies by providing better insights into customer behavior and preferences. This helps telecom companies make smarter decisions when it comes to marketing campaigns, product launches etc. It also boosts customer support services as better insights into what customers want allows them to provide better service at all levels. Moreover, with access to real time data about customers, operators can now use this information for targeted marketing campaigns which improve customer retention rates and increase profits (e.g., for example through upselling services).
  • Better Decision Making for Business Management: Telecom organizations can always analyze data to make more informed decisions. For instance, with access to large amounts of information about users and networks, operators can make better strategic decisions about their business operations such as pricing schemes and new product launches.

 

Best Practices for Implementation and Adoption

Industrial enterprises able to harness data and make it useful are likely to produce significant technology innovations in the years to come. Telecom infrastructure providers have an opportunity to be at the forefront of this wave of innovation. But as they turn their attention to data-driven solutions, they must first understand what it takes to adopt and deploy them effectively. To do so, telecom infrastructure providers should consider taking the following steps:

  • Collecting data sets in a structured way and within a proper big data infrastructure: To adopt and deploy data driven solutions, telecom infrastructure providers must first have access to a large volume of high-quality data. Structured data sources will allow them to easily interact with their customers and partners through software applications, thereby accelerating their ability to iterate on new ideas quickly. In this direction, state of the art big data platforms enable telecom providers to store structured data in a scalable and cost-effective way. They also provide tools that enable telecom enterprises to extract structured information from a variety of unstructured data sources, including text messages, images, audio and video.
  • Using appropriate technology with minimal latency between data collection and analysis: While many telecom companies have been collecting large amounts of data for years, processing it for analytics was often done using batch processing techniques that took hours or days to complete. Cutting edge big data technologies (e.g., streaming analytics toolkits) enable real-time processing that provides results in minutes or seconds. This is a key to improving responsiveness and supporting low-latency applications.
  • Defining the business questions that will drive their analytics: Telecom infrastructure providers need to start by identifying what they are trying to achieve based on the collection and analysis of data. A clear understanding of their business goals is therefore needed to guide them through the process of choosing the right tools and technologies for their needs.
  • Employing experts with the right skills (e.g., databases, analytics, machine learning, knowledge of the business domain): To develop, deploy and fully leverage data analytics projects, telecom organizations must employ experts with the right skills. For example, the data science team of the telco should have skills across various disciplines to ensure they can build accurate analytics models. Moreover, data scientists should also have experience working within the telecom industry to understand how things work on a technical level as well as how they impact customers’ experiences.
  • Create a culture of experimentation where ideas are tested quickly and iterated on based on results: Telecom companies must foster a culture of experimentation with data collection and analytics, which will enable them to implement “test and learn” cycles. The latter will boost continuous improvement of their data analytics capabilities.

 

Overall, most experts agree that data is powerful and consider applying data technologies to the telecom business. Modern telecom infrastructure companies and operators will gain a competitive advantage when they unlock the full potential of their data by transforming their business processes in data-driven direction. Using cutting-edge big data technologies most telecom organizations will become capable of building data-driven applications and of achieving a faster route to market for their new products.

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