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Internet of Things Makes Some Aspects of BI More Crucial

My favorite latest sensor, trakdot.com, lets me know where my luggage is when I land from an air flight. It’s just one in a myriad of devices in the Internet of Things, which delivers vast amounts of diverse information concerning surroundings, people and various assets. The IoT’s opportunities for businesses are exciting, and it’s already clear that sensor data is and will continue to be a game changer in many areas.

The Internet of Things makes business intelligence solutions and analytics essential, so we decided to explore the IoT implications in one of my recent #BIWisdom tweetchat sessions. We started with this question: What does the IoT do to BI corporate infrastructure?

Someone tweeted that it will challenge many legacy setups that were “built in knee-jerk fashion.” Another commented that the data preparation / modeling stage will be more crucial than ever before.

Then came another question: “Is the IoT a way that Hadoop will finally be accepted by many as part of the hybrid data?” Good question. We agreed that Hadoop will likely be a part of many IoT solutions in a growing mix of overlaying technologies, tools, concepts and methods.

And the age-old question of whether “ownership” of BI should reside in IT or the business units came up as someone queried: “Will the IoT drive BI back into the IT realm, or can it still be managed by the line of business?” Another participant in the group responded that the “extra layers of intricacy will probably drive it up to a C-level imperative for a while, which might help integrate with IT.”

As I shared with the group, from the research we conduct in our annual market studies, IoT BI so far is usually a line-of-business initiative driven by sales and marketing.

The nice thing about the IoT, tweeted a participant, is that it gets us even closer to where the data is generated and gives us access to data in real time. “Operational BI is the Holy Grail, and IoT helps get us there.” Someone else put it another way: “The beauty of the IoT and analytics is the volume of data from more sources. It will be easier to see repeat patterns and project what to expect, which will lead to better decision making.”

And that’s the challenge. How will we analyze the data that sensors bring us?"

The group quickly voiced their opinions and, as you can see, they weren’t all in agreement:
" “Raw data can definitely mislead the unqualified. It will be up to BI to add knowledge to produce intelligence.”
" “To analyze all that data in real time at massive scale, with value add, requires massive computing power – the cloud, for example. Or it will require streaming capability.”
" “A business may not want to land all the data, just the outliers.” 
" “But there has to be intelligence in the system to winnow out what the outliers are.” 
" “Maybe you land the abnormal patterns for a closer look and better predictive information.”
" “Reducing it to a subset will help with real-time data.” 
" “Agreed, but you still need processing power to determine what is abnormal. What if all sensors alarm at once, for example?”

Our #BIWisdom session concluded with two forward-looking comments. 
" “The data volume will be huge. I think businesses underestimate the impact on processes.”
" “There will be a lot of privacy concerns around the IoT data. As with any new technology, it can be used for noble or nefarious purposes. It will take a while for the laws to catch up – if they ever do.”

Bottom line: The possibilities of the good things that businesses and industries will be able to achieve through IoT data boggle the mind. But it comes with complexities and challenges.

Leveraging that data to advantage will require the entire BI analytics tool chest – descriptive, predictive and prescriptive tools. Most of all, the cloud is the key to the IoT. Many interesting data sources will be external to organizations and massive data will be stored in the cloud.

The areas of BI that will be most crucial in an IoT world are end user data preparation, predictive analytics, mobile BI, and location intelligence. In fact, the IoT will put location intelligence functionalities in the spotlight; this has been a BI sleeper until now.

There certainly will be a sea change in how we treat data, consumers, analytics and BI. Inevitably, we’ll be faced with good and bad effects from the IoT; regardless, businesses and BI teams must prepare for it.

Howard Dresner is president, founder and chief research officer at Dresner Advisory Services, LLC, an independent advisory firm. He is one of the foremost thought leaders in Business Intelligence and Performance Management, having coined the term “Business Intelligence” in 1989. He has published two books on the subject, The Performance Management Revolution — Business Results through Insight and Action, and Profiles in Performance — Business Intelligence Journeys and the Roadmap for Change. He hosts a weekly tweet chat (#BIWisdom) on Twitter each Friday. Prior to Dresner Advisory Services, Howard served as chief strategy officer at Hyperion Solutions and was a research fellow at Gartner, where he led its Business Intelligence research practice for 13 years.

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