How real-time analytics is enabling the growth of 5G

You may have noticed that 5G is here, there, and … well, not quite everywhere yet. That will change soon, with North American 5G connections projected to hit 215 million by the end of 2023, and 5.9 billion connections by the end of 2027. As of April 2023, there were 503 cities in the United States with access to 5G networks – the most of any country worldwide – and China was second, with 5G available in 356 cities.

As telecommunication companies work to overcome the current challenges to broader 5G coverage and adoption – such as the need for more cell towers and related infrastructure to provide smoother streaming, and the time required to license portions of the radio spectrum that 5G networks operate on – 5G should begin living up to its promise as a high data rate and low-latency technology. When fully deployed, 5G networks will allow rapid transfer of real-time data between two or multiple points, as well as previously impossible new applications for the workplace and home.

Meanwhile, it’s critical that businesses bring 5G services to market successfully, because these services will provide a foundation of ubiquitous connectivity with increased network capacity, throughput, and unprecedented responsiveness. That will drive newly enabled business models that prior generations of networks could not support. Network slicing, for instance, which allows operators to split a single physical network into many layers using a virtualized architecture, will become much more granular in a 5G world, enabling service providers to tailor connectivity to individual applications and users.

The role of real-time analytics in the 5G revolution

As Karl Whitelock observes in a recent brief from IDC, “It takes a mountain of data to deliver a quality customer experience in the 5G era.” Consider what’s behind that statement: The customer’s experience of using any 5G service or application will be critical to 5G adoption, and the insights required to continually improve customer experience must be based on the enormous volume of data that defines 5G operations. In other words, massive data sets are both the goal and the result. They’re generated by 5G networks, and they must be analyzed in real time to learn how customers use and adapt to the new services.

The long-established capabilities of OpenText analytics and AI offerings are already helping immensely with this essential requirement in the 5G era. OpenText™ Vertica ,for example, can handle more data, more queries, and more concurrent users than most analytics and AI platforms available today. The award-winning OpenText™ IDOL and OpenText™ Magellan™ unstructured analytics platforms reach beyond the structured data barrier to help deliver real- time data insights based on unstructured and semi-structured data. More on these components later.

As the popularity and usage of 5G grows, so will competition among network providers and operators. Real-time analytics will determine who can deliver the best customer experience based on actionable, data-driven insights in decision-making. Grounding those decisions on all available data – not just a down-sampled data set, which many vendors force business intelligence and data scientist teams to use – is the primary way OpenText analytics and AI technology can help competitors on the 5G landscape achieve accurate insights and predictions.

A look at 5G’s technical challenges

Optimal customer experience may be at the top of the list for business success as 5G gains adoption. But it’s not the only thing to factor into the new data analytics requirements. 5G networks and their vast data volumes pose new and unique technical challenges. The majority of these have to do with upgrades to the world’s existing infrastructure for telecommunications, as well as new security and privacy concerns.

  • The inevitable multi- and hybrid cloud future

Historically, communications service providers (CSPs) were slow to adopt cloud computing. As their customers have, in many cases, leap-frogged those CSPs in moving to the cloud, typically with multi-cloud operations, the cloud has become an inevitable player in the mix of 5G technologies. CSPs have some catching up to do. The widespread use of containers for data and app connectivity makes analytics all the more critical for 5G network operations.

  • Upgrading backhaul capacity

The backhaul is the portion of a telecom network that connects the core to the essential functions that accomplish the network’s purpose. Where fiber optic cable or other forms or hardwired connection is unavailable, the backhaul is a wireless connection. 5G networks require robust backhaul infrastructure to handle the increased data traffic and low latency demands. Upgrading the backhaul networks to support the higher bandwidth requirements of 5G can be complex and costly. But data analytics can help teams more rapidly locate trouble spots for prioritizing these upgrades.

  • Handling network slicing complexity

Network slicing has been used since the early 1980s – think modem communications, where bits transmitted at a given rate can travel along the same path as bits at different rates. A receiver understands only its assigned rate, thus there’s no signal interference, theoretically. Fast forward to now, and network slicing is used for entirely separate business models supported via optimized pathways that satisfy different consumer demands.
As IDC’s Whitelock explains it, “multiple customers will expect their network connectivity pathway and applications to perform in a certain manner that will be different from others. Customers will want the network to deliver value in different combinations.” Monitoring the new, extraordinary demands placed on the network requires high-speed, real-time data analytics that can deliver insights on performance. Improving the customer experience will boost loyalty and reduce churn.

  • Handling vast stores of data

Telecommunications companies accumulate vast stores of data, including:

  • Billing histories and email-based sales campaigns
  • IoT sensor data on network health
  • Customer service chat transcripts

The challenge is how to efficiently uncover emerging patterns and trends in these disparate types of data. The goals include improved service quality and better alignment with customer interests and demands; unlocking valuable insights in data; learning from past successes and failures to boost both profit margins and service quality; and finally, breaking down silos of data and to gain real-time visibility across the organization’s entire operation.

  • Security and privacy concerns

With the proliferation of connected devices and increased data traffic, 5G represents an increase in attack surfaces for DDoS and other forms of cyber attacks. Protecting user data and addressing potential vulnerabilities in the network will require real-time analytics that can detect intrusions and weaknesses instantaneously as they develop.

  • Accessing disparate data sources

Analytics users expect seamless unification of all interactions with data; data engineers, data scientists, and data analysts require a single environment where they can collaborate for the greater good of the enterprise. In the 5G era, gone are the days when analytics teams can afford the time it takes to transfer data to a central location for analysis purposes. This requires an analytics platform that can reach data anywhere it resides, and perform the analysis in place.

Consider how OpenText analytics & AI capabilities address the above requirements.

How the OpenText Analytics & AI platform empowers 5G adoption 

Comprising software products that over the years have evolved into best-in-class analytics tools, the OpenText Analytics and AI platform uniquely addresses the challenges of telecommunications service providers. They are used by industry-leading ISVs delivering next- generation solutions to carriers, especially those engaged with or preparing for 5G roll outs. 

Here are some of those capabilities:

  • Petabyte scale deployments at extreme performance to support low latency (speed of service) and 5G network slicing.
  • Cloud-native architecture, including separation of storage and compute layers, for all deployment options (off-cloud, public cloud, private cloud, hybrid), with support of all current S3-compatible object stores. Telecommunications providers gain a full range of options for data storage, and a cost-effective means for performing analytics.
  • Kubernetes operator and support of micro services to reduce energy consumption, infrastructure costs, and environmental impact.
  • Allow sentiment analysis based on unstructured data to understand customer behavior and respond quickly to changing business conditions.
  • Use predictive maintenance insights to keep repeater towers, satellites, and vehicles functioning optimally to reduce downtime.
  • In-database machine learning for increased network automation, zero human-touch network operations  
  • Ability to power new use cases such as predictive analytics and customer value management.
  • Improve customer satisfaction and retention through personalized usage reports viewable on any device
  • Tap into customer trends with AI-enhanced product recommendations, analytics and text mining
  • Uncover anomalies across operations, including disruptions in service
  • Accurately identify and profile market segments
  • Provision networks accordingly based on phone/network service forecast demands

OpenText customers are meeting today’s telecom demands

Recently, global telecommunications service provider Anritsu Service Assurance announced the launch of a new generation of analytical databases designed to meet the demands of 5G networks worldwide, based on the OpenText Vertica Analytics Platform. “The fast-paced evolution of 5G networks means service providers need to balance the network and operational demands at scale while ensuring their customers’ experience,” said Ralf Idling, CEO of Anritsu. “Vertica’s powerful database technology will be a valuable asset as we continue to help our customers deliver the highest levels of service quality to their customers.”   

Challenged to meet South Africa’s new law aimed at protecting personal information processed by public and private bodies, a major telecommunications company was determined to understand exactly what personal data was stored and where. Working with individual system owners, the data was extracted, deduplicated, and cleaned. It was then catalogued into an OpenText IDOL-based data repository where it could be searched, analyzed, and reported via user-friendly dashboards. “Before the …OpenText implementation, we would have to query hundreds of systems, search for a particular person’s data, manually collate that data, and create a response to a DSAR.” The IDOL implementation saved an enormous amount of time.

With more than 300 users requiring more than 200 separate reports daily, in departments as diverse as Infrastructure Expansion, Customer Services, and Network Management, a telecommunications giant based in Western Europe needed to retrieve, manipulate, and present vast amounts of data—quickly. Most importantly, the company wanted to schedule and deliver reports that users could access through a web-based interface. The Performance Analysis team opted for the OpenText Magellan BI & Reporting solution. Now, 95% of all reports are scheduled and delivered automatically. “Just in terms of my department, to produce the same volume and quality of reporting without OpenText would require a 50 percent greater headcount,” said the company’s Performance Analysis Manager.

Seizing business opportunities in the 5G era

Like many other technology revolutions, 5G represents a dramatic increase in speed and capacity. Just as railways of the 1800s delivered more goods to more places faster, 5G is enabling businesses to reach more customers with more services than ever before. Industries from automotive to healthcare, from financial services to hospitality and entertainment, are on the cusp of realizing the new benefits of 5G.

Data analytics is helping these businesses succeed in the early stages, and there’s much more to come as companies and consumers embrace the 5G revolution. The proven capabilities of OpenText analytics and AI products to deliver data-driven insights to business leaders across all industries are helping with that growth. As telecommunication companies look for superior data analytics technology to tackle the challenges outlined above, OpenText is ready to meet the demand and deliver the insights and data-driven predictions to help them succeed.

If your telecommunications business is looking for a proven, industry tested platform for superior data analytics, please book a consultation with the OpenText team to learn more!

Jeff Healey

As Vice President of Product Marketing, Analytics and AI, OpenText, Jeff leads product marketing for the Analytics and AI product group, which spans structured and unstructured analytics, data discovery, legal technology, OEM, developer, and APIs. With more than 25 years of high-tech marketing experience and deep knowledge of product marketing go-to-market planning and execution, Jeff comes to OpenText via the Micro Focus acquisition, where he was VP of Marketing for the Vertica product group. Previously, he led product marketing for Axeda Corporation (now PTC), the leading Internet of Things platform with millions of connected assets under management. Prior to Axeda, Jeff held product marketing, customer success, and lead editorial roles at MathWorks, Macromedia (now Adobe), Sybase (now SAP), and The Boston Globe.

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