Automation will help companies better monetize their big data and transform their economics in the coming year.
The recent past has been rife with activity aimed at achieving digital transformation outcomes using virtualization, automation, big data, AI, and analytics. Indeed, many companies have taken the mantra of using these capabilities to create personalized customer experiences, service agility, and business disruption to heart. They’ve been laying the groundwork for these outcomes by seeking ways to mine actionable insights from the large volumes of customer data they collect.
If the past few years have been mostly about gathering and storing big data, next year will see companies start monetizing that big data in much bigger ways as technologies emerge to 1) boost the productivity of data scientists, 2) automate a key aspect of machine learning, and 3) spur communications service providers (CSPs) to start riding the digital wave and exit the low-margin, pure-pipe business. All of these trends should make the job of turning data into more accurate decision-making and actionable business outcomes possible.
Specifically, here are three key trends on board for 2019:
#1: Companies will start deriving real value from big data, thanks to middleware that will take big data initiatives from pilots to production faster
The situation today: Big data has been a trend for several years. However, companies sitting on massive data stores, such as communications service providers (CSPs), have been challenged to monetize the data. One of the challenges has been getting the data they have collected into the correct format so that it is easily accessible and can be queried at a moment’s notice.
Data scientists face the challenge of integrating the company’s data storage repositories with the data science platforms they use for modelling and analysis. The process has involved building interfaces from each of the various repositories to each data science platform, one at a time. This manual and latency-prone practice has limited CSPs’ and others’ ability to mine actionable insights from big data that they might turn into personalized customer experiences, slicker operational processes, and other business outcomes that could add new revenue streams to their coffers or save them money.
What’s changing in 2019: Automating the data science process requires putting the modelling and analytics functions onto each data repository platform. To that end, middleware will debut in 2019 that integrates multiple data repository platforms, such as Amazon Web Services and Microsoft Azure, with multiple data science platforms, such as KNIME and H20.
The platform integration will collapse data silos and boost the productivity of data scientists, which will translate into more actionable insights for CSPs and other companies to use to monetize their data. To illustrate the integration impact: Let’s say a data scientist asks for five data attributes to run an algorithm, but these attributes don’t match the native storage formats of the various data types stored in the organization’s data lake. Yet - voilà! - the five attributes will nonetheless be delivered transparently to the scientist without the scientist having to endure the time- and labor-intensive process of reformatting the data. The result: accelerated results, decisions, and disruption.
#2: Machine learning deployments will be reinvigorated, as feature engineering becomes automated
Chief Architect & SVP of Technology,
The situation today: Feature engineering is complex, expensive, and time consuming, yet it’s a necessary and fundamental component to machine learning. It involves selecting the correct attributes of raw data to be fed into data models for analysis to yield accurate results.
Selecting the right attributes requires extensive domain expertise. It has also been largely a manual process. The code for manual feature engineering is problem-dependent, which means that it must be rewritten for each new dataset, rendering the process slow and error-prone. These issues have been difficult and costly, impeding the overall progress with machine learning and causing a number of pilots to fail or stall.
What’s changing in 2019: Feature engineering will become automated, extracting useful and meaningful features from a set of related data tables using a framework that can be applied to any problem. Time spent on feature engineering will be slashed, which will accelerate machine learning efforts and implementation times. Models will become adaptable: when data changes, it will trigger a features change, which, in turn, will trigger a model change. By reducing error, automated feature engineering will help prevent improper data usage that would invalidate a model and in doing so, drive better decision-making and, ultimately, help companies increase revenue.
#3: CSPs will start moving out of the pure-pipe business with a little help from predictive analytics
The situation today: CSPs are sitting on vast volumes of big data that they need to exploit to lower operational costs and to monetize their networks with completely new types of services and customer experiences. If they don’t use data-centric measures to get ahead of the game, they could be forever stuck in the pipe business, transporting bits, which relies on ever-shrinking margins for survival.
What’s changing in 2019: Smart CSPs will get creative about exploiting the data generated by network equipment and their subscribers. Web powerhouses have demonstrated how analytics can be used both to make money through targeted advertising, personalized services, and improved customer experiences that improve customer stickiness; CSPs will get on the bandwagon with these tactics to find and retain customers and enter new markets. They will likely be forming partnerships with companies in retail, banking, and other industries to create network-based services with a much bigger value add than simply data transport.
They will also begin to use predictive analytics and AI regularly to save money, as they make intelligent decisions about network traffic routing, device repairs, and SDN/NFV management. Predictive maintenance is a huge growth area as companies realize the cost savings of preventing problems rather than reacting to them.
As large companies and CSPs finally start making sense of their big data with smart tools that accelerate the creation of actionable insights with that data, the floodgates will open to business disruption. For its part, 2019 is likely to represent one of the early years where the digital transformation proof finally shows up in the proverbial pudding, as companies begin to monetize their big data in creative ways that have yet to be conceived.
Vodafone UK has launched VeryMe Rewards for its mobile customers.
It will use machine learning to tailor and personalise deals to meet individual tastes, with daily rewards including free treats, money off big name brands and one of the UK’s best offers for cinema tickets.
Current offers include two ODEON cinema tickets for just £7, which customers can use any day of the week, as well free Costa coffee and treats from Millie’s Cookies, Hotel Chocolat and Tesco. Other give-aways include 15% off Interflora and a three-month trial of The Mindfulness App. As an introductory launch offer, we will also give pay monthly customers an extra 2GB data when they sign up for VeryMe Rewards.
Customers simply need to download the My Vodafone App, click to join VeryMe Rewards and claim instant rewards. Over time the app will learn what customers like so that they don’t miss out on deals from their favourite brands. The My Vodafone App also allows customers to see their bill and how much data they have used.
To mark the beginning of the festive season, VeryMe Rewards will launch a selection of Christmas give aways throughout December.
The My Vodafone App can be downloaded from the App Store and Google Play Store.
NTT DOCOMO and Rohde & Schwarz have joined forces to set up the world's first ultra-wideband channel sounder for mobile communications exceeding 100 GHz.
They conducted radio wave propagation experiments at frequencies up to 150 GHz. The frequency bands from 100 GHz to 300 GHz are expected to enable further high-speed and large-capacity communications for the next generation beyond 5G.
In the experiments, the two companies measured and analyzed the effects of radio wave propagation characteristics and shielding effects in the mmWave range. As a result, they pioneered new frequency bands and contributed to the realization of terabit-class mobile communication systems.
In the 100 GHz to 300 GHz frequency bands, wider bandwidths are available than in those used for 5G. However, these higher mmWave frequency bands are strongly affected by persons, vehicles, trees and environmental conditions like rain. It is therefore necessary to research the influence of such objects on the radio wave propagation characteristics.
Using test and measurement equipment from Rohde & Schwarz, DOCOMO has developed a novel ultra-wideband mmWave band channel sounder to measure radio wave propagation characteristics necessary for evaluating mmWave mobile communication systems exceeding 100 GHz. The measurement parameters include the propagation loss (degree of attenuation of radio waves), power delay profile (arrival time of radio waves) and angular profile (indicator of spread of radio wave arrival). In the test system the R&S SMW200A signal generator together with the R&S SMZ frequency multiplier generate the mmWave bands, while the R&S FSW85 signal and spectrum analyzer equipped with the R&S FS-Z170 analyze it with a scalable wide analysis bandwidth of up to 2 GHz. The setup offers a highly convenient user interface with a high-resolution multi-touch display directly displaying the radio wave propagation characteristics in real-time.
In this experiment, this test system was placed in an anechoic chamber. DOCOMO and Rohde & Schwarz confirmed that they can measure and analyze the shielding effect of the human body, applying signals up to 150 GHz in all common 5G frequency bands currently in use or under consideration.
A new study from Juniper Research has found that annual online payment fraud losses from eCommerce, airline ticketing, money transfer and banking services, will reach $48 billion by 2023; up from the $22 billion in losses projected for 2018.
Juniper’s new research claimed that a critical driver behind these losses will be the continued high level of data breaches resulting in the theft of sensitive personal information.
Juniper claimed that fraudsters are using information gleaned from these breaches to move away from pure identity theft, instead using fragments of real data to create new, synthetic identities.With the global rise in instant payment schemes and a focus on transactional rather than behavioural risk, Juniper forecasts that money transfer would be particularly vulnerable, with fraud losses increasing by over 20% per annum to $10 billion in 2023.“Synthetic identity is currently the low-hanging fruit because, even though it takes time for fraudsters to establish, many of their targets are not set up to detect the behavioural giveaways that indicate this type of fraud. Fraud management providers have solutions on the market to combat this, but the industry as a whole is playing catch-up,”noted research author Steffen Sorrell.
Meanwhile, Juniper predicted that techniques practiced by the Magecart and Fin7 groups would become more common as fraudsters seek to create products from their knowledge. Here, the groups used a combination of malware and cross-channel approaches for criminal gain. The research noted, as a result, more complex fraud would only become more common as, in effect, a ‘fraud-as-a-service’ economy emerges.The report therefore recommended a holistic approach to fraud prevention. The procurement of omnichannel fraud prevention services and a strategy to assess and mititgate risk from a cybersecurity perspective will be critical for effective fraud prevention in the near to medium-term.Juniper Research provides research and analytical services to the global hi-tech communications sector, providing consultancy, analyst reports and industry commentary.
NTT DATA has entered into an agreement to acquire a majority stake in Atom Technologies, India’s leading end to end payment services owned by 63 moons technologies.
This earmarks NTT DATA foray into the rapidly expanding Indian payments market and the company aims to strengthen its business presence in the South Asian markets. NTT DATA is one of the largest IT companies globally with revenues of 19 billion USD. It has presence across over 50 countries and employs more than 120,000 globally. Its global payments division operates one of the largest payment operations in Japan.
Atom is India’s first company to have created a multi-channel payments platform covering POS, Online, IVR as well as Mobile. This partnership is a strong endorsement of the rapid strides made by the two countries in the digital sector and will help Atom to leverage NTT DATA’s presence across the globe and emerge as a large global payments entity. Utilizing NTT DATA’s relationship across the spectrum, Atom aims to further broaden its universe of customers both in India and globally.
Swiss operator Sunrise is going live with its second 5G network at Crap Sogn Gion and the LAAX ski resort.
Sunrise is providing Crap Sogn Gion and the LAAX resort with 5G antennas in the 3.5-GHz frequency range. The simplest type of 8x8 MIMO antenna now allows devices to reach bandwidths of over 300 Mbit/s. Once MIMO technologies with 32x32 and 64x64 antennas are used commercially, these devices will be able to reach bandwidths of over 1 Gbit/s, says Sunrise.
An increasing number of people planning skiing trips are now interested in taking virtual tours of their resort in advance. 360-degree live broadcasts of top events, including drone images, put prospective visitors in the mood for a skiing vacation. It may also soon be possible to take part in virtual ski courses, meaning guests will already have a good idea of how to maneuver on the slopes before they arrive.
Ericsson has been selected by Volvo Car Group (Volvo Cars) to provide the industrialized Ericsson Connected Vehicle Cloud (CVC) platform to further enable its digital vehicle services in more than 120 markets worldwide for the next five years.
Volvo Cars, like other major players in the automotive industry, is increasing focus on securing high-quality connected-vehicle services as digitalization increases the importance of software services. The services will also benefit from the increased speed, low-latency and capacity for mission critical applications, such as autonomous driving, that commercial 5G networks will enable.
The deal – which will enable Volvo Cars to provide car owners and drivers with its latest developments in connected car digital services such as automation, fleet management, telematics, navigation, and infotainment – is the largest to date for Ericsson Connected Vehicle Cloud.
Delivered via several geographically distributed centers, the platform takes full account of legal, security, and privacy obligations on a global scale – such as compliance with the European Union (EU) General Data Protection Regulation (GDPR).
With digital services increasingly becoming a differentiation factor for automotive consumers, the need for a secure and dependable service provision infrastructure is critical to provide quality of service at scale, says Ericsson.
Azerbaijan's Bakcell has released an important update for its 'My Bakcell' application, the first of its kind and most innovative customer care method on the country’s telecommunications market.
Thus, aiming to provide the customers with even more convenient and enjoyable user experience the Company has added Online Chat functionality to its “My Bakcell” app. By means of the Online Chat, Bakcell customers will be able to contact the operator in real-time and ask their relevant questions.
Not long ago, Bakcell has designed the “My Bakcell” – a virtual customer care application to provide the customers with a convenient, transparent and enjoyable user experience. This innovative e-care app allows the customers to perform all necessary transactions with mobile number, with no need for calling or visiting the customer care center.
By using 'My Bakcell', the customers are able to get detailed information about their number, including the remaining balance, active bonuses, dates of expiration, available megabytes of internet and etc. without a need to call or visit a customer care office.
Moreover, users of the new app enjoy a maximum level of transparency, being able to have a full access to their number’s usage history, covering the list of called numbers, time and duration of calls, as well as spent amounts and purchased additional services.
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