Although we've called 'continuous intelligence' by different names in the past few decades, the concept is important. Don't be distracted by the label. Credit: Thinkstock Buzzword alert: “continuous intelligence.” It’s fairly well defined on Gartner’s website. I also found an article in Forbes from almost four years ago that does a good job of explaining this “new” concept. The term “continuous intelligence” also pops up in some vendor marketing materials, and I often see it defined as something that’s focused more on operations and monitoring rather than on business processes. As a concept, continuous intelligence provides value to both. There is a wide range of opinions about what continuous intelligence means. My take is that it’s a design pattern that allows us to leverage real-time analytics to provide intelligence data for business- and operations-related processing that can process current data in the context of historical data, as well as apply real-time intelligence (AI and machine learning). In other words, continuous intelligence provides perfect, up-to-date, real-time data, along with real-time information about what that data means. Moreover, we leverage that current, meaningful, and intelligently augmented data within critical business processes so it can be more useful to automate a business, as well as optimize the business around any external changes. External changes could come from the market, customer behavior, system outages, supplier logistics, or anything else that could be a problem or an opportunity. Continuous intelligence concepts require a set of enabling technologies to drive them. These technologies typically include augmented analytics, event-stream processing, business rule management, and, of course, AI or machine learning. It could be anything that can aid in both delivering the right data to the right business processes and making sense of that data in flight without first having to send it to a data warehouse or data mart. The purpose of bringing up the “continuous intelligence” buzzword now is that I’m seeing “embedded intelligence” (my term) concepts arise that have many of the same patterns and business objectives. I come from a data-, application-, and service-integration background that started in the 90s. Even back then, many similar embedded intelligence concepts and their buzzwords were kicked around. These included “process-oriented enterprise application integration” (a term/concept I popularized), “the event-driven enterprise,” “the real-time enterprise,” “low-latency business processing,” and the “zero-latency enterprise.” I’ve seen new versions of embedded intelligence concepts emerge about every two years. They’re all a bit different in how they define the core value of leveraging real-time data intelligence within applications and business processes. Regardless, they have access to almost perfect information, and the core concepts are pretty much the same. Don’t get me wrong, I’m not trying to beat up the phrase “continuous intelligence” or any other buzzword. I just want to remind people that these emerging popular concepts are often much older and more pragmatic than we might realize. Also know that making up and/or repeating buzzwords is usually more distracting than productive. This is from someone who’s created a buzzword or two. Here’s what the next instance of the continuous intelligence concept will have that we haven’t seen in the past: First, realistic viability because we now have access to once-expensive technology resources via the on-demand value of cloud computing. Second, the use of true intelligence in flight due to today’s AI-based technologies that can process data as it appears. Finally, historical data storage that can be accessed in nanoseconds with some business intelligence database queries that once took several days to process. Although today’s continuous intelligence concepts and core business objectives are pretty much the same as they were in the past, it’s the enabling technology (the technology that makes it work) that finally evolved to make it all possible. Continuous intelligence, embedded intelligence, or whatever you want to call it, the enabling technology is finally cost-effective (cheap) enough for businesses to leverage these approaches as true force multipliers. The bottom line? Continuous intelligence is an aspect of cloud computing that needs to be understood and leveraged by most businesses if they plan to stay in business. Tossing out new buzzwords that mean basically the same thing as the last crop of buzzwords does nothing to get us closer to widespread understanding of this problem and potential solutions. Let’s clear out the white noise and keep the continuous intelligence concepts—or whatever you want to call them—in sight, including the core value. Hyped phrases and acronyms just make us look silly. Related content news Go language evolving for future hardware, AI workloads The Go team is working to adapt Go to large multicore systems, the latest hardware instructions, and the needs of developers of large-scale AI systems. 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