The Importance of Enhanced Data in AIOps Success

The Importance of Enhanced Data in AIOps Success

CSPs need curated data to monetize 5G network use cases.

Communications service providers (CSPs) increasingly are turning to the creation of artificial intelligence for IT operations (AIOps) teams to position themselves to drive next-generation automation and monetization use cases for 5G standalone (5G SA) and beyond. To facilitate this objective, AIOps needs "high-fidelity" data to improve network performance, reduce downtime, and enhance the overall customer experience.

Armed with the right data, AIOps will be able to analyze customer data to gain insights into their behavior and preferences, enabling CSPs to offer more personalized services and ultimately help improve network promoter scores. New frontiers AIOps will be able to impact include improving network operations efficiency at the RAN-CORE-MEC, identifying patterns and anomalies, and driving monetization use cases that go beyond network data analytics function (NWDAF).

AIOps will also be able to identify security threats in the wireless network, deliver enterprise 5G SA service slicing assurance, monitor usage and make traffic pattern predictions for roadway analytics, and facilitate traffic and network planning to better optimize underutilized resources.

Although these use cases are promising, the success of AIOps in moving them forward will depend entirely on the quality of the data being used.

Data Alone Isn't Enough. Quality Matters!

The good news is that the 5G SA network is littered with hidden gold in the form of network-level data that must be mined and refined in a way that is consumable for AIOps engines. Packet-level data gathered in a big data lake is simply not enough on its own. The challenge AIOps faces with this unrefined data is that it is not real time, which is needed to drive modern software-defined services. Also, massive volumes of network-level data take a very long time to assemble and analyze. What's worse, the data is not always provided in an easily consumable standard open format.

Additional challenges include insufficient focus on application quality of experience, by user and by service; a lack of correlation of user identification to the data, service, and application the user is utilizing; a lack of understanding of how network services are being utilized down to a user or enterprise level; and an inability to know how security issues are affecting the network and user experience. Ultimately, the inability to see the network end-through-end leaves AIOps with "piecemeal data." Context is needed in order to know what the data really means-the who, what, when, and where-along with the network conditions that are affecting the network quality being provided to each subscriber. AIOps needs smart visibility!

The Need for Smart Visibility

NETSCOUT addresses the AIOps need for smart visibility. By tapping into a common source of truth, NETSCOUT is able to combine packet-level data with telemetry and visibility from system elements. Because packet-level data is available universally, across all borders, in the same form and semantics, NETSCOUT is able to illuminate trouble spots anytime, anywhere throughout the 5G network. The intelligence delivered by this approach allows AIOps to focus on proactive detection versus reactive mitigation.

By creating what we call Smart Data at the source, NETSCOUT is able to send high-fidelity data through the AI pipeline to an AIOps environment. Armed with this near-real time curated data, AIOps is then positioned to drive high-level business use cases for the CSP. This will allow CSPs to focus on areas of monetization potential, such as connected and autonomous vehicles, contextual advertising, patient monitoring, real-time manufacturing, security video analytics, cloud gaming, and smart city traffic management.

Additional opportunities to monetize 5G networks might include tourism via venue analytics, area analysis, and targeted hotel and restaurant offers. Smart Data can be used to bolster marketing through analytics of retail locations and store visitor activities. It can be used for mobile advertising, location promotions, and out-of-home analytics as well as for geomarketing, customer care, and location-based charging. There is further monetization potential in finance, helping to fight credit card fraud, improving transaction verification, and reducing insurance fraud.

Providing a Clean Data Stream for AIOps Success

NETSCOUT's intelligent solutions deliver the Smart Data that AIOps needs to run efficiently and make critical decisions in near-real time. By sifting through terabytes of data and delivering a curated, clean data stream that is highly relevant, AIOps gains the visibility needed to drive new initiatives for customers. Going a step further, CSPs can take advantage of NETSCOUT visibility that has been combined with other data, such as the integration with ServiceNow's IT Operations Management (ITOM). NETSCOUT's nGeniusONE service dependency data mutually enriches configuration management database (CMDB) information from ITOM-and vice versa-to continue reducing mean time to repair (MTTR) even further and accelerate smarter outcomes.

As CSPs increasingly look to AIOps to improve monetization opportunities, NETSCOUT is poised to deliver the data needed to achieve success.

To get AIOps now visit this page: Next-Level AI for Telecom Networks | NETSCOUT