Trends 2021 Tips on how the telecommunications industry can invent
The telecommunications sector has undergone through the corona-pandemic recovery. Companies should use the momentum to lift your own Transformation to the next level. The aim of innovative, sustainable, and digital business models.
Telecommunications companies not to operate long-only and mobile networks, or Internet access, as well as radio signals. In the course of digitization, the industry has established services for video telephony, IPTV, Video-on-Demand or music streaming, competing with the Offerings of Internet companies. More and more devices to produce ever-increasing amounts of data, which for telecommunications companies offers the Chance to transform modern Communication Service providers (CSP) to. These are understood as providers of new digital technologies and services in the Smart City, Smart Home, Autonomous driving cars and networked production (“industry 4.0”) is used. What is crucial is the development is driven, in addition of 5G.
The new mobile phone standard that offers data rates of up to 10 gigabits per second, which, in the future, much more data in real time to be streamed. This data must accumulate in a CSP, before he can analyze it with conventional Data Warehousing solutions and Dashboards, and for new digital Services. Finally, the business model of digital, where all other industries are working intensively. Especially the pharmaceutical and chemical industry as well as IT and telecommunications are grown in the Corona of a pandemic is the fastest. Here, almost half of the companies reported according to a Bitkom survey in each case of any progress. The potential economic success for CSPs, especially on the digital fields of application such as analysis of the customer experience, cyber security, and in the context of IoT (Internet of Things) – but only if you bring with you certain skills.
1. Multi-function-analysis of the data
CSPs produce today large amounts of valuable data. You have profiles, access to detailed customer, content preferences and usage patterns, as well as device-, network-, location-, Sensor -, and App-usage data. Your task is to collect each of these data types to process, store, and analyze. It doesn’t matter where the data originates and whether it is collected at the Edge, in your own datacenter, in a Public or Hybrid Cloud, generated, processed, or stored. The company must be able to quickly gain insights and use cases from a set of static values and dynamic data – the closer to real time, the better. Machine Learning (ML), advanced Analytics and artificial intelligence (AI) to identify patterns in Petabytes of data, detect anomalies, and make predictions. Several methods of analysis must be able to simultaneously access the same data basis.
2. With a cross-data platform Silos break
However, the necessary multi-functional analysis in the telecommunications sector is not yet part of the Standard. Often analytical Workloads to run in Silos. Thus, the outlined intelligent data analysis recognizes the relationship of different data to each other across the entire enterprise, there is a need for a cross-data platform. In question is a Public Cloud Service, as this provides the necessary agility and flexibility, as well as the data density scores.
Platforms based on Open Source and an open analysis Framework, to meet the requirement profile. These solutions run in any Public Cloud as well as locally in the data center or Private Cloud environments. It is also important that you allow regardless of the environment in a consistent common security and Governance and enforce policy. In the closer selection of a platform comes out, if you a analysis of the spectrum is over the entire data life cycle, which is at least equivalent to or better than each of the individual Silo solutions.
Telecommunications companies have a comprehensive, Cloud-enabled platform in use, the multi-function analysis enables you can represent new applications, you your operating costs significantly lower, or new revenue opportunities.
3. Personalized customer experiences that count
In customer service it’s about customer profiles and usage data, network metrics, performance, location data and Social Media Streams together. The following multi-function analysis capable of predicting, for example, customer churn and Take suitable counter-measures. It is also possible to personalize and target marketing can be then campaigns. This is exactly the aim of Telefónica in Spain, followed with a scalable Cloud platform on which more than 100 applications are running. The technology Stack collects, stores and analyzes, for example, customer interaction and experience data. The real-time insights into customer behavior help to provide personalized experiences by, for example, that are appropriate to the TV content to be played out. After you Implement the technology, customer usage increased by 20 percent. The customers were clearly satisfied, and the outflows decreased.
Comparable experiences of the Deutsche Telekom. The Provider uses the Cloudera Data Platform, in order to draw more value from its data. It is used for fraud detection, as well as the improvement of the customer relationship management (CRM), network quality and operational efficiency. Through the application of machine Learning and artificial intelligence, the company’s network identifies problems before customers notice them, and can identify fraud patterns, and real-time threats before the business is affected. In addition, the improved data analysis led to a deeper understanding of the wishes of the customer. On the Basis of these insights, Deutsche Telekom optimizes your campaigns, what the revenue has also boosted. At the same time, the customer was able to reduce churn by up to ten percent.
4. At a higher Cyber-security level
The security experts of the CSPs need access to a flood of data, including network protocols, event and Streaming data, as well as inventory and configuration data in real time and analyze them. Only then will you be able to recognize risks and incidents in time to respond. The best support of data platforms, the ML and AI functions make find anomalies and unusual activities such as fraud in real-time warn. In addition, the technology aims to reduce false alarms, and both unknown as well as known types of Fraud to identify. Because Roaming, subscription, and service fraud and other scams cause significant revenue losses.
5. The own Position in the IoT environment, use
The telecommunications industry can form in a figurative sense, the connectivity layer for the rapidly growing IoT Ecosystem. It is located in the favorable Position between the Sensors and the users, in order to integrate data, to aggregate and at the same time safety and analysis. Customer location information, demographic data and preferences of the customers are incorporated with, in the future, data analysis Service, (C) for the retail, financial services, advertising, health care and public administration are conceivable. With Petabytes of data, the stream Sensors in real time, to drive CSPs are already Developing IoT use cases for industrial IoT, E-Health, telematics, utilities, and consumer IoT. The demand for data management and analysis services, however, will only continue to grow, as soon as these offers are Mature.
Re-inventiveness is in demand
The telecommunications company’s data platforms are available that bundle all the necessary ML and AI functions for a multi – functional analysis of the entire data life cycle. No matter whether companies get started with Analytics for customer churn, to Target Marketing, fraud detection, or for new IoT applications – the advantages are obvious. The telecommunications industry needs to recognize in which position it is in, in order to accelerate your Transformation. This also means that your company will be re-define, if not as CSPs re-invent.
Alexander Zschaler, Regional Sales Director Germany at Cloudera.