A number of Wi-Fi analytics tools have been brought to market over the past few years, and while most organizations have yet to dip their toes in the Wi-Fi analytics waters, our research shows that those who have are realizing significant benefits.\nTo be sure, there\u2019s still lots of room for innovation in Wi-Fi analytics, but the glowing reviews we\u2019ve received in our interviews with network practitioners across a wide variety of industries and applications indicate explosive growth ahead over the next few years.\nWhile the two terms are sometimes used interchangeably, it\u2019s important to understand how analytics is different from analysis. Analytics applies \u201cwhat-if\u201d thinking to very large problems that would otherwise be intractable. Whereas analysis is appropriate for bounded, well-understood problems, analytics can be applied in situations where you don\u2019t know what you\u2019re looking for \u2013 and can do so with the speed and flexibility that is essential in network operations today and, in most cases, beyond the capabilities of human information processing alone.\nIt\u2019s easy to see how analytics can be applied to Wi-Fi networks. While suspect behavior almost always triggers an exploration of the data available, the sheer volume of information, even in mid-sized networks, generally precludes a quick conclusion. The quickest path to extracting meaning and value from all that data, and setting upon the optimal path to a solution to what might seem like a simple problem at the time \u2013 but which often morphs into very long weekends looking through logs and settings \u2013 is the right analytics tool.\nAs we learned from our conversations with those already putting Wi-Fi analytics to work, the solution to any given problem often leads well beyond the common and the obvious, and with the constant pressure to minimize time-to-solution so as to keep networks on the air today always motivating innovative productivity-enhancing strategies and solutions, Wi-Fi analytics brings exactly what\u2019s needed to the table.\nWidespread knowledge and understanding of the technologies and strategies of network analytics today remains limited, as is to be expected in any new field of technical endeavor. So, in an effort to close this knowledge gap, we decided to take a look at how an investment in acquiring, learning, and applying Wi-Fi analytics tools is benefiting operations teams.\nWe interviewed IT professionals at four different organizations, asking three fundamental questions: Why did you make the investment in network analytics? What problems are you solving that couldn\u2019t be addressed before? And what additional network analytics capabilities would you like to have going forward?\nHere\u2019s what we learned.\nUniversity of Washington troubleshoots Wi-Fi\nDavid Morton is director, networks and telecommunications, for the University of Washington. David and the IT Infrastructure team are responsible for wired and wireless networks at the university, plus university hospitals, the state\u2019s K-20 school networks, and more. The network includes 12,000 APs and serves more than 80,000 unique users per day and a few hundred thousand devices connecting per week.\nMorton noted that as his networks continued to grow in scale and complexity, more issues and problems were appearing than were being reported. With Wi-Fi access becoming mission-critical, he needed better methods for finding and fixing problems, proactively if possible.\nHe chose Aruba\u2019s NetInsight analytics tools to help him identify specific problems and recommend solutions.\nFor example, a \u201cclicker\u201d application that enabled students to answer questions in class was not working properly, but with only 40-50 out of 400 students in larger classrooms being affected, identifying the cause was very difficult. Multiple classrooms had the same problem, but the affected user base varied without a pattern.\nA check of the management console revealed no obvious issues, so Morton used NetInsight to analyze across clients, controllers and destinations. He discovered that the issue was multi-faceted: a Wi-Fi configuration change was indeed required to balance users across radio channels, but the primary cause was localized to a cloud-based third-party software service provider, which required additional scale in their infrastructure along with bug fixes.\n\u201cWe couldn\u2019t have found this without [NetInsight],\u201d Morton said, \u201cand now that [NetInsight] knows about the problem, it will automatically report if it recurs again \u2013 at the UW, or even another [NetInsight] site.\u201d Morton finds great value in the tools' cloud-based, multi-client nature.\nGoing forward, Morton wants to be able to unleash the tool to find actionable insights from data already present within the network, and to automate responses via management-console feedback. He\u2019s also looking for more nuanced intelligence as networks continue to increase in capacity.\nNVIDIA seeks a holistic network view\nJohn Kilpatrick is senior network architect at NVIDIA, a company that specializes in graphics, AI and high-performance computing. His primary responsibilities include wireless and the enterprise access layer of the firm\u2019s network. NVIDIA has 15,000-20,000 global concurrent clients and 3,000 APs, and they use Nyansa Voyance for analytics.\n\u201cWe\u2019re making a very significant investment in improving wireless infrastructure,\u201d Kilpatrick said. \u201cWe regularly ask ourselves what can we do to ensure the best quality of experience for our users. So, we need an analytical, data-driven approach to quantifying the user experience in terms of throughput, capacity and coverage.\u201d\nKilpatrick said he has seen a broad range of problems in network operations over the years, including in such functions as DHCP, authentication and onboarding. \u201cIt was difficult to see the nature of a given problem before we installed Nyansa, and the problems weren\u2019t always wireless. These could include a bad browser version, unpatched security flaws, a slow DHCP server and many more.\u201d\nInstalling the Nyansa software enabled a more holistic view of the network. \u201cI use it every day, and it makes my job so much easier.\u201d\nHis ongoing goal is to know about problems before users are affected. And he\u2019s interested in enhancements that enable more operational data to be integrated into his analytics solution, such as Cisco Service Assurance, software agents on clients, and integration with enterprise mobility management (EMM) solutions. Standards and APIs for analytics are also of interest at NVIDIA.\nOptix Media improves performance\nShane Moulton is president of Optix Media, LLC, a managed ISP with a focus on student apartment complexes. The firm provides a turnkey Wi-Fi service, emphasizing customer service, partnerships and long-term relationships with property developers and managers. The scale of operations is national, with 6,000 APs and around 120,000 connected devices.\nStudents can be a very demanding audience. \u201cOur customers expect perfection,\u201d Moulton said. In an effort to meet that goal, Optix Media is using the analytics capabilities built into the Mist Systems management software.\n\u201cWe originally got involved with Mist because we view them as an innovator, but not specifically for their analytics,\u201d Shane said. Optix Media deployed the Mist solution at their biggest pain point, a residential complex with 900 students.\nThe use of analytics has indeed proved quite valuable. \u201cWe made a change to the network and found a DHCP error right away,\u201d Shane said. \u201cWe were impressed with the very rapid time to solution, much better than we\u2019ve ever seen in the past.\u201d\nAnalytics is now essential for all new deployments, having been used to resolve other problems such as client driver issues, wireless incompatibilities, and older devices causing slow performance.\nLooking ahead, Shane said the \u201csoftware needs to be as smart as the tech support people,\u201d a direction he mentioned Mist is pursuing. \u201cWe need to have wireless tools that are as good as those on wire, and analytics must be as integrated as possible into every Wi-Fi network.\u201d\nUniversity of Mount Union moves toward a self-managed network\nTina Stuchell is executive director of Information Technology, and Dave Smith is assistant director of IT for Technical Services at the University of Mount Union, in Alliance, Ohio, a school with about 2,200 full-time-equivalent students, each using three to five devices, often simultaneously. The school operates more than 1,300 APs, including a stadium with guest access.\nThe school\u2019s objective is to cover the entire campus with high Wi-Fi density to ensure sufficient capacity for their demanding student audience. They bought the Extreme Analytics tool when it was introduced a few years ago as one of the first analytics products to hit the market.\n\u201cOur goal always is to optimize user experience,\u201d Smith said. \u201cWe\u2019re always asking ourselves how we can further improve our operations. We need more productive troubleshooting and more efficient operations, and the improved visibility that comes from having a great analytics capability helps us in being proactive.\u201d He added that they installed analytics during a major network refresh, an opportune time to explore new innovations.\nAs an example of the value of analytics, Stuchell and Smith mentioned a problem they were experiencing in application latency \u2013 specifically, why Netflix would occasionally be buffering or dropping connections.\n\u201cIs the problem inside the campus network, at our ISP or at Netflix itself? Given the massive amount of data to plow through, analytics has proven itself essential in dealing with problems like these. We also like having a customizable dashboard, the ability to identify malware and spam-related issues quickly, and being able to do rapid traffic-pattern analysis alone more than justifies the investment,\u201d Stuchell said. \u00a0\u201cWe\u2019ve improved time-to-solution and our ability to be proactive well in advance of any impact on our user community.\u201d\nLooking ahead, \u201cthe graphic displays and monitoring are helpful and informative, but analytics tools in the future need to do more than just provide logs, graphs and charts,\u201d Stuchell said. \u201cThey need to alert us before the end-user experiences a problem and give us exact steps to fix the problem \u2013 or, better yet, automatically address the problem even if working with other systems such as policy, DHCP, etc., is required.\u201d\nSmith added that he isn\u2019t quite ready for analytics to, for example, shut off a switch port, but such an action with operator-in-the-loop approval would be fine.\n\u201cNetworks just need to run, with little to no operator intervention,\u201d Stuchell said. \u201cThey really need to be as self-managing as possible, making changes automatically. Analytics moves us towards that goal.\u201d\nWhat vendors need to do\nAnalytics is adding significant value in the shops we spoke with, and undoubtedly many more. As we learned from our conversations with users, though, there are a number of issues and opportunities that require action on the part of the vendor community:\n\nStandards \u2013 There\u2019s a need for more open access to raw data from vendors. Knowing where the data is and how to interpret that data is critical. Open standards for device-specific access to operational data would certainly help, but developing them will be daunting without appropriate standards and vendor cooperation.\nData completeness and validity \u2013 A major concern is validating the integrity, completeness, and interpretation of the data points involved. That old saying, \u201cGarbage in, garbage out,\u201d still applies, and automated analytics-driven decision-making will be impossible without this matter being resolved.\nAutomation \u2013 We also see a clear need for a closed-loop feedback mechanism between analytics and settings within the management console. As analytics evolves from reactive to proactive, the focus will shift from what\u2019s happening to what might happen and perhaps even will happen, a scenario we find realistic given advances in machine learning. Visual reporting will remain vital, but automatic actions are clearly within the realm of possibility \u2013 even probability, as networks become too complex for real-time human-in-the-loop management. Standards will also play a big role here.\n\nThe gradual transition to software-defined networking (SDN) now underway presents a very broad opportunity to address many if not all of the above.\nThere\u2019s also a clear emphasis on the importance of cloud-based implementations and even multi-client cloud-services implementations of analytics. This is an exciting opportunity in that patterns of behavior noted at one client might indicate at least the possibility of a similar or related challenge at another \u2013 and often well before operations teams or end-users might otherwise take notice. There is, of course, the potential for new privacy and security concerns arising in this context, but it\u2019s very likely that acceptable solutions to these challenges can be found.\nDue to the size, scale, and the mission-critical nature of the majority of Wi-Fi networks installed today, it\u2019s clear that ever-more powerful analytics tools are well on their way to a position of prominence within the arsenals of network operators everywhere.\nWe are especially intrigued with the possibility of enhanced machine-learning-based automation via a feedback loop between analytics and management consoles. This could even extend to, for example, operations-policy, security and overall network upgrades being driven by analytics.\nAs Wi-Fi analytics seems destined to evolve from a separate function and ultimately disappear into the network management woodwork, the benefits we\u2019ve just begun to explore will clearly become even more visible \u2013 and valuable \u2013 in the years to come.