By Bill Franks, Apr 12, 2018
As the Internet of Things (IoT) continues to explode, so does the need for the analysis of IoT data. At IIA, we call the analysis of IoT data the Analytics of Things (AoT). There are many success stories from the world of AoT. However, without some attention to standards of both IoT data itself and the analysis of it, organizations will struggle to achieve AoT’s potential. In this post, we’ll dig into several different areas where standardization must be pursued.
By Bill Franks, Mar 08, 2018
Within a two- to three-year span, Artificial Intelligence (AI) has gone from relative obscurity to an extreme level of industry attention and media coverage. As a result, organizations that barely knew how to spell “Artificial Intelligence” a few years ago are now charging full steam ahead to pursue AI initiatives. A common question that is raised is, “Why is now the time for AI?” After all, there have been bursts of hype around AI multiple times over the last few decades. Is today different? And, if so, why?
By Bill Franks, Feb 08, 2018
Certainly, it is important to have analytics available in the timeframe needed for making decisions. For many years, it was too difficult and expensive to execute analytics anywhere near real-time and so everything was done using infrequent batch processes. As processing power has increased exponentially and costs have dropped to unprecedented levels, it is feasible to perform a wide array of enterprise analytics on a near real-time basis. However, many organizations today are vastly over-utilizing real-time analytics and are paying a price for it that, unfortunately, isn’t always recognized.
By Bill Franks, Jan 11, 2018
Any new tool or technology has the potential to be put to use for good purposes or, unfortunately, for harmful purposes. Artificial intelligence is no different. As we see the rapid progress occurring in the AI space, lots of attention has been paid to all of the good uses of AI. However, it is inevitable that those with nefarious intent are also studying AI successes with an eye toward how to twist them into tools to pursue their less than honorable goals.
By Bill Franks, Dec 14, 2017
Last week, IIA hosted our annual Predictions and Priorities webinar, as well as the associated research brief. When we sat down to determine what we should focus on this year, Tom Davenport and I both immediately raised a trend that we’ve recently been discussing with organizations. After reconciling our semantics, we realized that we were both excited about the same base trend. I want to reiterate it here as I think it is a critical trend to understand and adapt to. Namely, “the post-algorithmic era has arrived”.
By Bill Franks, Thomas H. Davenport, Robert Morison, Dec 07, 2017
Available to Research & Advisory Network Clients Only
Each year, the International Institute for Analytics takes time to focus on the latest analytics trends and the most pressing analytics challenges currently facing organizations. We gather the basis for our predictions from our day-to-day work supporting and advising analytics leaders and programs. Our insights arise from the breadth of expertise and cross-industry perspectives we receive every day from our clients, partners, and members of the IIA expert network. This is our 8th annual look forward into the upcoming year.
By Bill Franks, Nov 09, 2017
The concept of a blockchain is quite a phenomenon in recent times. It has quickly risen from a relatively obscure idea known mostly within some small circles to one that is being discussed as having potential to literally change some of the fundamentals of the world’s economic systems.
By Bill Franks, Oct 12, 2017
The breadth of analytics has certainly increased in recent years. So, too, has the pool of people who dip their toe into creating analytics of one sort or the other. The trends toward democratization of data and self-service analytical capabilities are powerful and both have driven a lot of value for organizations in recent years. At the same time, it is possible to go too far.
By Bill Franks, Sep 14, 2017
There seems to be some confusion as to exactly what artificial intelligence (AI) is, and how the discipline of AI should be categorized. Is AI a form of analytics or is it a totally new discipline that is distinct from analytics? I firmly believe that AI is more closely related to predictive analytics and data science than to any other discipline. One might even argue that AI is the next generation of predictive analytics. Additionally, AI is often utilized in situations where it is necessary to operationalize the analytics process. So, in that sense, AI is also often pushing the envelope of prescriptive, operationalized analytics. It would be a mistake to say that AI is not a form of analytics.
By Bill Franks, David Alles, Aug 16, 2017
Available to Research & Advisory Network Clients Only
As we reported in Strata Hadoop World 2017 – Big Data and Analytics Developments from the Heart of Silicon Valley, O’Reilly’s Strata Conference already has a heavy focus on machine learning and AI. What makes O’Reilly AI unique, versus Strata, is its exclusive focus on AI and the inclusion of more cutting-edge AI research topics that have huge potential, but are further from commercialization. The objective for this report is to summarize the common themes and key trends emphasized at O’Reilly AI into an easy-to-read guide that can serve as both a general reference and a resource for planning AI initiatives. With this in mind, the report is organized into seven sections.