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What is Advanced Network Analytics? Cutting Through the Hype

Shamus McGillicuddy

Everyone wants to talk about how analytics is the future of network engineering and operations. The phrase "network analytics" is used by vendors of various stripes to imply that a particular technology is smarter and better than the average solution.

But what is it? What does the term network analytics mean to the enterprise network infrastructure professionals?

Enterprise Management Associates (EMA) recently published survey-based research on this topic. We sought out individuals who were actively involved in so-called network analytics initiatives. To find these people, we presented random IT professionals with a broad definition of a network analytics initiative.

"The implementation of technologies and strategies aimed at extracting previously unrealized insight and value from data produced by and collected from network infrastructure and network traffic. Network analytics supports network and IT engineering and operations use cases. It can also benefit the business via business process optimization and other opportunities."

To qualify for our research survey, IT professionals had to work for an organization that was engaged in an initiative that fit the above definition, and survey respondents had to be directly involved in such an initiative.

Our first goal with this research was to let survey respondents tell me what network analytics means to them. And that’s where the following question comes in.

What network analytics technology strategies does your organization currently use or plan to use?

The average respondent selected slightly more than two of the following multiple-choice options, which suggests that network pros are taking multiple paths toward a network analytics future.

1.Analytics features embedded in network infrastructure (58%)

2. Analytics features embedded in network operations software (56%)

3. Packaged solutions from pure-play network analytics vendors (55%)

4. Packaged solutions from pure-play general analytics vendors (34%)

5. Standalone analytics stacks (homegrown or otherwise) applied to a network data store (18%)

We also asked them to select the one option above that was their primary approach to network analytics. Analytics features embedded in network operations software was the top choice (40%), analytics embedded in infrastructure was second (30%), and pure-play network analytics vendors was third (18%).

This data tells us that IT shops are consuming network analytics from some very familiar vendors. In fact, you might already have your network analytics solution.

Network monitoring tools increasingly leverage new analytics and machine learning algorithms to make their tools more intelligent and useful

Network management software vendors and network hardware vendors are delivering analytics technologies within their existing product portfolios. We’ve seen indications of this for a few years now. Network monitoring tools, for instance, increasingly leverage new analytics and machine learning algorithms to make their tools more intelligent and useful.

Network infrastructure vendors are embedding analytics everywhere, particularly in the data center and the WAN. Nearly every enterprise-grade software-defined WAN (SD-WAN) solution leverages analytics in some way, particularly those with sophisticated traffic steering capabilities and extensive network automation capabilities.

Yes, there are clearly specialized network analytics solutions out there for you to buy, and many enterprises are doing so. But you don’t need to add another vendor to your roster to access the benefits of network analytics today. You may not even have to buy a new product. Your existing vendors are enriching the technology you have already deployed.

The network hardware you already have installed may get smarter in the next few years thanks to new analytics features. The network management and monitoring tools that you have also will get smarter. If it hasn’t happened already, you can expect to see your existing solutions enhanced by process analytics, predictive analytics, data mining, trending, and emulation. And you will also see your vendors leverage machine learning to make their products smarter.

As this industry trend unfolds and embedded analytics proliferate in hardware and management software, some network managers may see gaps in their engineering and operations processes that a solution from a pure-play network analytics vendor can fill. More than half of the IT professionals we surveyed have apparently already responded to this issue by engaging with such analytics vendors.

This research tells us that network analytics isn’t some shiny new thing that you need to buy. It’s more about an evolution and enrichment of existing technology. As you navigate your way around the hype machine, keep that in mind.

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What is Advanced Network Analytics? Cutting Through the Hype

Shamus McGillicuddy

Everyone wants to talk about how analytics is the future of network engineering and operations. The phrase "network analytics" is used by vendors of various stripes to imply that a particular technology is smarter and better than the average solution.

But what is it? What does the term network analytics mean to the enterprise network infrastructure professionals?

Enterprise Management Associates (EMA) recently published survey-based research on this topic. We sought out individuals who were actively involved in so-called network analytics initiatives. To find these people, we presented random IT professionals with a broad definition of a network analytics initiative.

"The implementation of technologies and strategies aimed at extracting previously unrealized insight and value from data produced by and collected from network infrastructure and network traffic. Network analytics supports network and IT engineering and operations use cases. It can also benefit the business via business process optimization and other opportunities."

To qualify for our research survey, IT professionals had to work for an organization that was engaged in an initiative that fit the above definition, and survey respondents had to be directly involved in such an initiative.

Our first goal with this research was to let survey respondents tell me what network analytics means to them. And that’s where the following question comes in.

What network analytics technology strategies does your organization currently use or plan to use?

The average respondent selected slightly more than two of the following multiple-choice options, which suggests that network pros are taking multiple paths toward a network analytics future.

1.Analytics features embedded in network infrastructure (58%)

2. Analytics features embedded in network operations software (56%)

3. Packaged solutions from pure-play network analytics vendors (55%)

4. Packaged solutions from pure-play general analytics vendors (34%)

5. Standalone analytics stacks (homegrown or otherwise) applied to a network data store (18%)

We also asked them to select the one option above that was their primary approach to network analytics. Analytics features embedded in network operations software was the top choice (40%), analytics embedded in infrastructure was second (30%), and pure-play network analytics vendors was third (18%).

This data tells us that IT shops are consuming network analytics from some very familiar vendors. In fact, you might already have your network analytics solution.

Network monitoring tools increasingly leverage new analytics and machine learning algorithms to make their tools more intelligent and useful

Network management software vendors and network hardware vendors are delivering analytics technologies within their existing product portfolios. We’ve seen indications of this for a few years now. Network monitoring tools, for instance, increasingly leverage new analytics and machine learning algorithms to make their tools more intelligent and useful.

Network infrastructure vendors are embedding analytics everywhere, particularly in the data center and the WAN. Nearly every enterprise-grade software-defined WAN (SD-WAN) solution leverages analytics in some way, particularly those with sophisticated traffic steering capabilities and extensive network automation capabilities.

Yes, there are clearly specialized network analytics solutions out there for you to buy, and many enterprises are doing so. But you don’t need to add another vendor to your roster to access the benefits of network analytics today. You may not even have to buy a new product. Your existing vendors are enriching the technology you have already deployed.

The network hardware you already have installed may get smarter in the next few years thanks to new analytics features. The network management and monitoring tools that you have also will get smarter. If it hasn’t happened already, you can expect to see your existing solutions enhanced by process analytics, predictive analytics, data mining, trending, and emulation. And you will also see your vendors leverage machine learning to make their products smarter.

As this industry trend unfolds and embedded analytics proliferate in hardware and management software, some network managers may see gaps in their engineering and operations processes that a solution from a pure-play network analytics vendor can fill. More than half of the IT professionals we surveyed have apparently already responded to this issue by engaging with such analytics vendors.

This research tells us that network analytics isn’t some shiny new thing that you need to buy. It’s more about an evolution and enrichment of existing technology. As you navigate your way around the hype machine, keep that in mind.

Hot Topics

The Latest

Enterprises are under pressure to scale AI quickly. Yet despite considerable investment, adoption continues to stall. One of the most overlooked reasons is vendor sprawl ... In reality, no organization deliberately sets out to create sprawling vendor ecosystems. More often, complexity accumulates over time through well-intentioned initiatives, such as enterprise-wide digital transformation efforts, point solutions, or decentralized sourcing strategies ...

Nearly every conversation about AI eventually circles back to compute. GPUs dominate the headlines while cloud platforms compete for workloads and model benchmarks drive investment decisions. But underneath that noise, a quieter infrastructure challenge is taking shape. The real bottleneck in enterprise AI is not processing power, it is the ability to store, manage and retrieve the relentless volumes of data that AI systems generate, consume and multiply ...

The 2026 Observability Survey from Grafana Labs paints a vivid picture of an industry maturing fast, where AI is welcomed with careful conditions, SaaS economics are reshaping spending decisions, complexity remains a defining challenge, and open standards continue to underpin it all ...

The observability industry has an evolving relationship with AI. We're not skeptics, but it's clear that trust in AI must be earned ... In Grafana Labs' annual Observability Survey, 92% said they see real value in AI surfacing anomalies before they cause downtime. Another 91% endorsed AI for forecasting and root cause analysis. So while the demand is there, customers need it to be trustworthy, as the survey also found that the practitioners most enthusiastic about AI are also the most insistent on explainability ...

In the modern enterprise, the conversation around AI has moved past skepticism toward a stage of active adoption. According to our 2026 State of IT Trends Report: The Human Side of Autonomous AI, nearly 90% of IT professionals view AI as a net positive, and this optimism is well-founded. We are seeing agentic AI move beyond simple automation to actively streamlining complex data insights and eliminating the manual toil that has long hindered innovation. However, as we integrate these autonomous agents into our ecosystems, the fundamental DNA of the IT role is evolving ...

AI workloads require an enormous amount of computing power ... What's also becoming abundantly clear is just how quickly AI's computing needs are leading to enterprise systems failure. According to Cockroach Labs' State of AI Infrastructure 2026 report, enterprise systems are much closer to failure than their organizations realize. The report ... suggests AI scale could cause widespread failures in as little as one year — making it a clear risk for business performance and reliability.

The quietest week your engineering team has ever had might also be its best. No alarms going off. No escalations. No frantic Teams or Slack threads at 2 a.m. Everything humming along exactly as it should. And somewhere in a leadership meeting, someone looks at the metrics dashboard, sees a flat line of incidents and says: "Seems like things are pretty calm over there. Do we really need all those people?" ... I've spent many years in engineering, and this pattern keeps repeating ...

The gap is widening between what teams spend on observability tools and the value they receive amid surging data volumes and budget pressures, according to The Breaking Point for Observability Leaders, a report from Imply ...

Seamless shopping is a basic demand of today's boundaryless consumer — one with little patience for friction, limited tolerance for disconnected experiences and minimal hesitation in switching brands. Customers expect intuitive, highly personalized experiences and the ability to move effortlessly across physical and digital channels within the same journey. Failure to deliver can cost dearly ...

If your best engineers spend their days sorting tickets and resetting access, you are wasting talent. New global data shows that employees in the IT sector rank among the least motivated across industries. They're under a lot of pressure from many angles. Pressure to upskill and uncertainty around what agentic AI means for job security is creating anxiety. Meanwhile, these roles often function like an on-call job and require many repetitive tasks ...