From rapidly evolving technologies to stiff competition, there’s nothing simple about the wireless industry.
Take 5G. Whether deciding where to locate a complex web of new infrastructure or analyzing performance and service levels, the common element in all of the challenges the telecom industry faces is data — petabytes of it.
Data flows within the industry are orders of magnitudes greater than just a few years ago. And systems have become faster. This puts a premium on smart, quick decision-making.
Collecting and normalizing huge network datasets is just the start of the process. The data also has to be analyzed. To address these issues, wireless carriers like Verizon and data providers like Skyhook are turning to data analytics accelerated by the OmniSci platform and NVIDIA GPUs.
OmniSci, based in San Francisco, pioneered the concept of using the incredible parallel processing power of GPUs to interactively query and visualize massive datasets in milliseconds.
NVIDIA is a partner of and an investor in the company through NVIDIA Inception GPU Ventures. OmnSci is also a premier member of NVIDIA Inception, a virtual accelerator program that enables startups with fundamental tools, expertise and go-to-market support.
Composed of a lightning-fast SQL engine along with rendering and visualization systems, the OmniSci accelerated analytics platform allows users to run SQL queries, filter the results and chart them over a map near instantaneously. In the time it takes for traditional analytics tools to respond to a single query, the OmniSci platform allows users to get answers to questions as fast as they can formulate them.
The extreme parallel processing speed of NVIDIA GPUs allows entire datasets to be explored — without indexing or pre-aggregation. Analysts can create dashboards composed of geo-point maps, geo-heat maps, choropleths and scatter plots, in addition to conventional line, bar and pie charts.
Even non-technical users can query and visualize millions of polygons, based on billions of rows of data, at their own pace. Enhancing the interface, the RAPIDS machine learning framework enables users to create predictive models based on existing data.
Ensuring the rollout of even coverage for wireless customers requires coordinating a huge number of new cellular base stations — in everything from cell towers to homes and businesses — as well as new distributed antenna systems for major indoor and outdoor facilities.
Wireless providers must also continually monitor and analyze network performance; surges and anomalies have to be identified and quickly addressed; and equipment must be constantly optimized to meet customer demands. Additionally, cybersecurity defenses require a never-ending cycle of management, reviews and upgrades.
Accelerated analytics helps wireless carriers solve many of these difficult operational problems. For network planning, GPUs offer much deeper analysis of market utilization and can spot gaps in daypart or geographic coverage. Log queries can be reviewed within moments, instead of hours, and help predict usage in specific geographic areas to better inform engineering or utilization planning decisions.
To ensure optimal service levels of customers, engineers are using GPU-accelerated analytics to better understand network demand by parameters such as daypart, service, and type of data. They can review these metrics in any combination and at any level — nationwide, regionally or even at street level — with results plotted in fractions of a second.
On the business side, marketing and customer service personnel require improved ways to attract new customers and reduce subscriber churn. Where prepaid wireless is the norm, it’s vital to introduce services that generate incremental revenue while reducing turnover.
With OmniSci, these teams can review mobile and application data to identify opportunities for promotions or upselling and to reduce customer churn. Location, activity and hardware profiles can all be taken into account to improve ad targeting and campaign measurement.
Verizon, America’s largest telecom with over 150 million subscribers, uses the OmniSci platform to improve its network reliability.
Anomalies are identified in just moments, versus old methods that would take 45 to 60 minutes, leading to faster problem resolution. Verizon also uses OmniSci to uncover long-term trends and to facilitate the expansion of its Wi-Fi services into new venues such as sports stadiums.
Skyhook, a mobile positioning and location provider, uses OmniSci to cross-reference Wi-Fi, cellular and sensor data to provide precise information about users and devices. Retailers, to cite one example, use this intelligence to analyze store visits and shopper behavior patterns. The data also helps with customer acquisition, site selection and various investment opportunities.
Skyhook’s insights further aid in the creation of location-based experiences such as customized storytelling and venue orientation. When disasters strike, the company’s real-time knowledge base helps first responders understand complex damage scenarios and to move quickly to locations where help is needed most.
Rather than mustering a little more performance out of legacy systems, new challenges require new solutions. OmniSci and NVIDIA are helping telcos answer the call.