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Analytics 3.0: Cisco Leaps in at the Edge

Cisco unveiled its analytics strategy with its Connected Analytics portfolio, pulling useful information from the data where it’s being gathered rather than from data warehouses or data lakes.

Edzard Overbeek, senior vice president, services, Cisco
Edzard Overbeek, senior vice president, services, Cisco

As Cisco considers its path of innovations past, the company—largely known for its network solutions—is looking for its north star for future growth. “We’re talking about not change at a factor of 2X, but X squared,” said Cisco chairman and CEO John Chambers. The missing piece for Cisco, as Chambers sees it, is analytics.

That’s the piece that will let Cisco be one of the fewer than 40 percent that survive an economy changing at lightning speed; a company that reinvents itself constantly to keep up in an increasingly digital world.

“The way you think exponentially about market possibilities is key,” Chambers said. “You have to think differently, you have to structure yourself differently. You have to think about what portions of your business are in exponential growth, and what portions are in linear growth.”

Chambers was talking to industry editors recently to announce Cisco’s comprehensive data and analytics strategy and solutions portfolio. Cisco Connected Analytics are a series of portfolios that include easy-to-deploy software packages to bring computing and analytics to the data, rather than bringing data to a data warehouse or data lake.

What Cisco refers to as the Internet of Everything (IoE) is the rapidly expanding ecosystem of connected people, processes, data and devices. So far, though, analytics solutions have been applied mainly to data created within an organization’s four walls, and located in a centralized data store. Cisco’s idea is to bring those analytical capabilities directly to the edge, where the data is being gathered.

“There is a massive shift in the market where the remote device at the edge is quickly becoming an incredibly strategic tool to share and collect data, enable more informed decision-making, and deliver the best customer experience possible,” said Edzard Overbeek, senior vice president, Cisco Services, who also spoke to industry press. “But if customers don’t have the right analytics solutions in place to make sense of it, that data is useless.”

Cisco sees that the analytics model today is challenged. Decision-makers are struggling with how to make sense of the data and use it to their advantage, while IT managers are struggling to provide the business with all the data they need in real time. A new Cisco study finds that 40 percent of survey respondents regard the inaccessibility and inability to interpret data as the biggest obstacle to translating connections into actionable insights. Cisco Consulting Services also estimates that analytics will drive $7.3 trillion of the $19 trillion IoE opportunity over the next 10 years.

The data coming from an oil rig provides a good example of the data conundrum companies face today. A typical offshore rig can generate up to 2 TB of data every day. “The majority of this data is time-sensitive to both production and safety. Yet it can take up to 12 days to move a single day’s worth of data from its source at the network edge back to the data center or Cloud,” noted Mala Anand, senior vice president, Cisco Services, in a blog about Cisco’s announcement. “This means that analytics at the edge are critical to knowing what’s going on when it’s happening now, not almost two weeks later.”

The solution to such an issue is not just increasing the bandwidth for the data, but changing the decision about what data needs to make it through. “Don’t send the data back to the data center; just make sure the oil field keeps producing,” Overbeek commented. As long as the data is within range, it just keeps operating, he explained. “But if it turns into red, you want the signal as fast as you can back into your data center so people can look at that.”

Cisco’s new analytics solution combines intelligent networks and infrastructure with data virtualization to enable customers to access highly distributed data, while adding analytics capabilities to extract valuable insights. The Connected Analytics for the Internet of Everything portfolio is being rolled out for several different verticals. There’s Connected Analytics for events, for retail, for service providers, for IT, for network deployment, for mobility, for collaboration, and for contact centers.

For example, Connected Analytics for IT provides business intelligence and insights to help align IT capabilities such as data management and data governance with business objectives. Analytics could be applied to align implementation of new IT capabilities such as deploying collaboration technology in new branch offices or by understanding evolving security requirements in real time so organizations can mitigate risk by improving cybersecurity.

Cisco is leaping into what it considers Analytics 3.0. As Overbeek explained it, many companies start with Analytics 1.0, in which they become more intelligent based on historic data. “There are big data fields that we can take a look at, but it’s looking back in the past to get a look at the future,” he said.

Analytics 2.0 starts to embrace the concept of data lakes, which makes it easier to throw all kinds of data into one place—both structured and unstructured data—and make sense of it.

“And here we are today,” Overbeek said. “The Internet of Everything is what we’re at the very core of. The immense amount of data these devices and sensors are generating, do we need to bring all that data back to the data warehouse? It’s not possible.”

Analytics 3.0 is the real-time streaming of data. “The combination of Analytics 1, 2 and 3 is the future,” Overbeek said. “If you think about the opportunity of everything being connected to data, the core of analytic data needs to be at the edge.”

“It’s about intelligence throughout the network. Intelligence all the way at the edge,” Chambers added. “It isn’t about connecting things. It isn’t just about the data. It is about how do you take this and really make it intelligent throughout the environment.”


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