Real-time data and streaming analytics

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On a recent hiking trip, I was reminded of the growing importance of real-time data and streaming analytics.

One of the downsides to hiking in the rural mid-western United States is spotty cell reception. The positive spin is you get to spend time in nature without the constant distractions of checking emails, text messages or Facebook status updates. On the negative side, you can lose GPS location tracking and directions, and you can't send texts or calls if someone gets lost or hurt.

My hiking group naturally splits in two: One with the more advanced or adventurous hikers who want to hike off-trail or over more challenging terrain; and one with the less experienced or simply casual hikers who want to stick to the well-worn trails and not wander too far from where we parked the cars. I was with the advanced group.

Weather prediction is problematic – a fact we were reminded of on this hike. While the initial weather forecast showed very little chance of rain, the late spring weather can change with little to no warning in our area. As our two groups hiked away from the cars, it was blue skies and sunny. Entering the woods brought welcome shade, but also blocked our view of dark clouds slowing approaching on the horizon. And the trail map we had downloaded that morning quickly proved to be of little use, since a storm from a few weeks ago had caused flash flooding – and downed trees forced my group to venture even further off the beaten path than usual. We were relatively deep in the woods when the thunder started to rumble to our south (the direction of our cars). Looking up through the gaps in the tree canopy was confusing – from there, it was still blue skies and sunny.

No cell signal, no GPS: The downsides of guessing

Normally the radar tracking on my smartphone weather app would provide real-time updates of the storm cell racing toward us. But with no cell reception, all it could display was the morning’s radar data, which showed clear skies. Its center point was the last location where I'd had a strong signal, which was 10 miles from where we parked. Zooming out, I could see a storm system far to the south of us, which I thought must have been pushed in our direction by a strong northern wind.

Then the rain began, slowly at first – but steadying to the point that its impact on the trees above was louder than the thunder. At first we decided to seek tree cover and ride out the worst of the rain. But the ground all around us was getting very muddy. Guessing that we were less than three miles from the cars, we decided to head back before the footing got much worse. In was slow going and we got very wet – but we made it back to the cars in about an hour.

Unfortunately our other group was nowhere to be found. Without cell reception, texts or calls were pointless – so we waited. Thankfully we had the cars for shelter, because the storm continued for another hour and a half and brought torrential rain and flash flooding. After the storm had passed without the other group returning, I drove away to find somewhere nearby with cell reception. After about 20 minutes, my phone was flooded with a torrent of text messages from the other group. Although they thought they were going in the right direction to get back to the cars, but they had actually headed into the storm’s path and gotten completely turned around. They ended up at a campground's outdoor storm shelter six miles west. Fortunately, the shelter was close enough to a cell tower to give consistent reception, so they realized they needed to stay put and hope that someone from our group would get their texts and come pick them up. Eventually, of course, we did.

Lacking the analysis of streaming real-time weather data sucked the fun out of my hiking trip. Without streaming data analytics, businesses aren't going to find it fun competing in today’s rapidly evolving business world. In this world, there's no room for guessing and winding up on the wrong path. Businesses must be able to access and make the best use of all available data – so they can move quickly from insight to action, make sound, data-driven decisions, and adapt to ever-changing business conditions.

Download a paper: Channeling Streaming Data for Competitive Advantage
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About Author

Jim Harris

Blogger-in-Chief at Obsessive-Compulsive Data Quality (OCDQ)

Jim Harris is a recognized data quality thought leader with 25 years of enterprise data management industry experience. Jim is an independent consultant, speaker, and freelance writer. Jim is the Blogger-in-Chief at Obsessive-Compulsive Data Quality, an independent blog offering a vendor-neutral perspective on data quality and its related disciplines, including data governance, master data management, and business intelligence.

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