Weather predictions, APIs, IoT, and a powerful digital platform for your uninterrupted Business

This article was originally published on IBM Big Data Hub.

Many of us seem to watch weather forecasts to figure out what to wear the next day but forget about it right after that, unless of course there is snow in the forecast. Especially here in the northeast; we dread watching the weather report for about six months of the year.

For this reason, IBM’s acquisition of The Weather Company was a head-scratching moment for many because we are used to only the consumer aspect of weather, not the business side—especially given the high speculation by The Wall Street Journal.

Why did IBM, an IT software company, go after The Weather Company then? IBM started this fundamental shift a few years ago, transforming itself from a big IT and mainframe provider to a digital, data and insight company. Recent speeches by the CEO of IBM clearly articulate its main focus has shifted toward cognitive computing, analytics, IoT, APIs, hybrid cloud and digital platforms that support big corporations to reinvent themselves and engage in the digital economy.

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Digitizing Healthcare, Because Our Lives Matter

This article originally appeared on IBM Big Data & Analytics Hub.

The United States spends around 17-18% of its GDP on healthcare every year. When you put this into dollar numbers, it is a mind-boggling $2.9 trillion.

Unfortunately, that spending will grow at a faster rate now due to baby boomers becoming an aging population, and they are the largest demographic in the U.S. (Baby boomers are about 76 million, which accounts for 25% of the population of the U.S.). The healthcare related spending is expected to grow at a faster pace than the under 5% annual rate it grew over the last decade.

Unless the U.S. gets this spiraling healthcare spending under control, in a few short years we will be spending almost 25% of our entire GDP in healthcare trying to fix people’s failing health, instead of spending it somewhere else where it is desperately needed. Obviously, we can’t stop the aging population, but we can make the healthcare system more efficient. Overall, chronic diseases account for about 86% of the health care spending in USA. Severe chronic conditions such as heart disease, arthritis, asthma and diabetes alone cost 33% of the total spending.

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Success of Data Insight–Driven Enterprises in Digital Economy

This article originally appeared on IBM Data Magazine.

Connecting everything to the Internet—the Internet of Everything—brings an interesting problem to the forefront: data onslaught. Examples of data onslaught in the new digital economy includes the 2.5 quintillion bytes of new data collected every single day (and it is expected to increase three times by 2017), or the 2.5 PB of data collected by a major retailer every hour or the fact that by 2015, 1 trillion devices are expected to be connected to the Internet and generate data for consumption.

A key point that almost every organization seems to miss in the data economy is that just because they are collecting so much data doesn’t mean they are collecting the right data, or even enough data. They may be either collecting very little of something very important or not collecting the right data at all. Even more appalling are situations in which organizations collect huge amounts of data and do absolutely nothing with it. People often make the mistake of connecting value with voluminous data.

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Going beyond the mobile app gold rush

Recently, I wrote a blog on What powers the mobile economy?which created lot of interesting conversations. A few large enterprise customers reached out to me and suggested they can relate to things I said in my post. In my follow-up conversations with them, a couple of more interesting views came up.

Sadhu-baba-with-mobile-funny

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Did Germany Cheat in World Cup 2014?

– By Andy Thurai (@AndyThurai)

This blog originally appeared on BigML blog site.

Now that I got your attention about Germany’s unfair advantage in the World Cup, I want to talk about how they used analytics to their advantage to win the World Cup—in a legal way.

player-performance

I know the first thing that comes to everyone’s mind talking about unfair advantage is either performance-enhancing drugs (baseball & cycling) or SpyCam (football, NFL kind). Being a Patriots fan, it hurts to even write about SpyCam, but there are ways a similar edge can be gained without recording the opposing coaches’ signals or play calling.

It looks like Germany did a similar thing, legally, and had a virtual 12th man on the field all the time. For those who don’t follow football (the soccer kind) closely, it is played with 11 players on the field.

So much has been spoken about Big Data, Analytics and Machine Learning from the technology standpoint. But the World Cup provided us all with an outstanding use case on the application of those technologies.

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I am an IBMer…

As I indicated earlier, I left Intel to pursue an outstanding opportunity in the same space. I know I kept this as a surprise while I went on vacation and didn’t write much, which led to some speculation on where I was going…so here it is. I am going back to IBM after being away for four years – a (sweet) homecoming of sorts :).

When I left Intel, I was seriously considering another opportunity, equally good. But I got to talk to some of my old pals at IBM and learned that they were looking for someone with my skills. Couldn’t hurt, I thought, talking to them. Well, now I am an IBMer!

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Enterprise IOT: Mixed Model Architecture

– By Andy Thurai (@andythurai)

This article was originally published on VentureBeat.

Recently, there has been a lot of debate about how IoT (Internet of Things) affects your architecture, security model and your corporate liability issues. Many companies seem to think they can solve these problems by centralizing the solution, and thus collectively enforcing it in the hub, moving as far away from the data collection centers (not to be confused with data centers). There is also a lot of talk about hub-and-spoke model winning this battle. Recently, Sanjay Sarma of MIT, a pioneer in the IoT space, spoke on this very topic at MassTLC (where I was fortunate enough to present as well). But based on what I am seeing in the field, based on how the actual implementations work, I disagree with this one size fits all notion.

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