How predictive analytics gives government agencies a head start

What is Network Analysis?

Network analysis is about seeing the big picture. It’s like an airport control tower.

“A good scan tool will provide visibility across the entire network, from the wireless edge to the data center and into multicloud or SD-WAN environments,” said David Savage, vice president of sales at Extreme Networks.

The key is automation through machine learning. Aruba tracks network activity for over 100,000 customers in a data lake.

“We pretty much mirror the market,” says Larry Lunetta, vice president of wireless LAN and security solutions marketing at Aruba. “As a result, we can zero in on a customer network, profile it, look at the data parameters, and see if that network is optimized.”

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Machine learning uses standard network behavior as a reference to spot and report deviations. This information is displayed on a dashboard that allows administrators to track everything in real time, and network administrators can customize the information they receive.

“If you don’t want to watch something, you can actually set the rules for what you want to watch,” says Brent Potter, global government strategist for Cisco.

Cisco’s DNA Center product provides a dashboard that enables network design, creation of user and device policies, and rapid provisioning. It can also be used to model speed changes. “So we’re going to add this new equipment to the heart of the infrastructure,” says Potter. “What’s going to break?” »

Network operators can pre-provision to avoid potential outages.

What is Predictive Network Analytics?

Predictive analytics is the use of big data, statistical algorithms, and machine learning to identify possible future events based on historical information. It’s as close to a crystal ball as you’ll find in networking technology.

“By taking baseline data and applying it to future scenarios, predictive analytics tools can identify when a scenario is likely, such as a potential entry point for unauthorized network access or when unusually heavy network traffic can start causing problems for users,” Extreme Networks told Sauvage.

Extreme Networks offers a sandboxing platform that creates a digital twin, a simulated network based on artificial intelligence that includes data traffic. “IT teams can run potential scenarios in an inconsequential environment and determine what actions they would take in advance,” Savage says.

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Keep in mind that, like weather forecasts, predictive analytics isn’t always perfect.

“Algorithms are mathematical constructs that run on massive amounts of network data, examining many variables in your network, applications, and internet paths,” writes JP Vasseur, a machine learning researcher at Cisco, in a blog post. “It is important to understand that predictions may be incorrect and may not account for certain scenarios.”

So we have to be realistic. “We should expect there to be limits to predictive analytics, but at the same time, that doesn’t stop us from extracting the full potential value we can get,” Vasseur writes.

Ashley C. Reynolds