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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The “Ugly Duckling” API syndrome

Ugly Duckling lookingAs an advisor and a digital strategist, part of my role is to talk to customers about their APIs, IoTs, and their overall digital strategy. After conversations with a lot of them, one thing stands out: Almost everyone thinks their API is awesome. While a good portion of them are very impressive, and some are moderate to good, I do see a bunch of ugly ones too. However, if you are a producer — whether it is a movie, a baby, or an API – it will be hard for you to realize, admit, and come to terms with your “Ugly Ducklings.” Obviously, the amount of sweat and tears that went into your initiative causes you to look at your APIs through beer goggles, which makes them look good in your eyes, even if the APIs are mediocre.

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Bringing your ideas to life in digital economy

Bringing your life-changing ideas to fruition needs a different mindset (and toolset) in the digital economy. The need for speed with digital innovation is more important than ever, with every start-up trying to push the envelope with their new ideas.

Remember the good old days, when you had an idea and tried to prove that concept by doing a POC (Proof of Concept)? While the POC technically stands for proving a concept, most times it is done as a proof of technology. We try to figure out a way to incorporate this newer idea into an existing IT infrastructure, often failing, and trying to make it work. I still remember the days in which we used to wait for the security admins to open the appropriate ports and give us the right access before we could even start to “install” our software to try things out. Those days are gone!

In the digital economy, once you get an idea, you cannot afford to sit around and build it for years, not even months, like legacy enterprise software.

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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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Is your API an asset or a liability?

This article was originally published on VentureBeat.

A touchy API topic is data ownership and liability, regardless of whether the APIs are open or protected. Obviously, depending on your business model and needs, you will choose to expose the APIs and the underlying assets to your developers, partners, public developers, your consumers, or others that I am forgetting. While almost everyone talks about the API business relationships, the liability concern brings the legal relationship to the forefront.

[Image courtsey: jasonlove.com]

liabilityAPIs are considered a contract between the data supplier (or API provider) and the app provider. If you have different API providers that publish APIs from a central place, and multiple third parties use that API catalog to build apps for their consumers (end users), then it becomes complicated. While you can fix some of this by writing detailed contracts and making the app providers and end customers agree to the terms of usability before they use those APIs, as a provider, you are also responsible for implementing controls around your APIs to mitigate most, if not all, of the risks involved.

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Are Public APIs Going Away?

This article was originally published on LinkedIn Pulse.

You might have noticed in the news recently that ESPN has shut down its public API program. According to ESPN, they are trying to “better align their engineering resources with their core product development,” though the actual reason seems to be that they want better control over their unique and licensed content, and better monetization, which public APIs may not offer.

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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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