Tuesday, 4 February 2014

Internet of Things & Big data Analytics

We have entered the Digital Enterprise era.  All the businesses are aiming at reaching their Customers anywhere, anytime, any platform with any device.  All such smart devices or physical objects that are connected to internet & are continuously emitting data and communicating with each other is called Internet of Things (IoT).

You will find all these objects around you in your day. Your Fitbit wrist band is monitoring your sleep, waking you up at desired time, tracks your activity. When you go out for walking or jogging in the morning, your Nike shoes with built-in-sensor are collecting all the data and track your time, distance, pace & calories burned. 

All this humongous data is ideal candidate for Big data Analytics. Let us see how does 3 V’s of Big data comes into this scenario. All the data which is generated by these devices or things is voluminous or recurring at specific intervals.  This streaming data is “always in motion” so there is a velocity.  The variety is coming from all different sensors sending data.

Big Data will help make companies smarter, more progressive and give them a business advantage. You can have better control over your business with IoT by better tracking and better reporting. Let us see some examples.

Sigalert.com provides sensor based analysis of traffic on highways.  This when combined with Waze, a world's largest community-based traffic and navigation app, helping drivers avoid the frustration of sitting in traffic, cluing them in to a police trap or cutting 5 minutes off of their regular commute by showing them new routes they never even knew about. 

Great River Medical Center is one health care organization that's connecting many of its medical devices into a network using Microsoft's Windows Embedded, thereby enhancing the patient care by speeding delivery of medications, reducing an average 1.5 hour wait time, down to just 30 minutes. Getting the correct medication to patients faster has improved patient outcomes and reduced the rate of readmission.

With the Loxone iPhone app you can access, monitor and control your home from anywhere.

A food distribution company can use sensors in trucks that send temperatures, humidity; point to point travel times back to data center for further analysis.

Today's tech-savvy consumers have the option to shop whenever and wherever they want, including on mobile devices.

Retailers have lot of use of IoT & Big data. They can measure the real time customer traffic in & out of store with video cameras, current queue lengths, historical transaction data & footfall data to predict how many more checkouts to be opened. This helps improve the customer experience.

Utility companies have installed smart meters to monitor energy, water & gas consumption.

Airbus A380 has sensors that monitor the wear and tear of the flight in real time which helps in preventive maintenance of parts before they fail and increase operational efficiency.

As IoT becomes mainstream, it can play a big role into areas such as supply chain management. When customers' preferences or needs can be tracked in real time, businesses have the opportunity to react accordingly and immediately, with options such as dynamic messaging, pricing, or service delivery.



10 comments:

  1. Excellent post :) I like the various use cases across industries. I bet that IoT would become so pervasive in the near future that everyone would take this for granted.

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  2. Nice article! I feel like big data is everywhere. I always get big data ads, in fact, when I search for big data on google! Pentaho and Jaspersoft ads are constantly popping up on pages that are completely unrelated to big data. It just goes to show that the Internet is tracking me during my searches and tries to market ads according to my web viewing! Open source BIRT and BIRT Analytics can be used to handle Big data analytics (www.actuate.com/products/birt-designers/birt-designer-pro/). The thing I like about open source software is that it allows developers to use the code and create applications their clients need. It just democratizes software in that regard and BIRT helps people access and use big data in reports. But, in light of the NSA using the metadata and getting in trouble for using it, who owns big data? It is just OUT there, everywhere! It feels like the IoT has created a monster out of data, data retrieval, data privacy, data rights.

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  3. Good read, enterprises with high tech infrastructure are quick to adopt and foresee big data analytics as advantage. The issue arises when the pitch is made to a organisation who's existing infrastructure is archaic and they have very few data sources that can be mined. So when we say we can monitor the real time logistics, they think "ok, our trucks don't have those sensors" and suddenly the realization sets in that this activity will require them to make lots of investment. But saying that (big) data analytics will become mainstream as data warehousing, due to the fact enterprises will upgrade the infrastructure sooner or later.

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  4. Nice article. Efforts appreciated.

    A philosophical point of view if I may call it so. Are we (as a global community) trying to analyze too much? Should we not let life be as it should be? Being "in the present", not following the trend (aka Big Data Analytics) and not knowing future is where the real beauty of life is.

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  5. Thanks for sharing the great stuff.

    In today's IT environment with a data overload, the ability to discover distinct ideas enables businesses to enhance decision making, leading to the ability to capitalize on chances, lessen risks, and manage costs effectively. Big data analytics is about managing organizing big data and generating new insights and making business decisions driven by data.

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  7. Nice article! Enterprises with high tech infrastructure are quick to adopt and foresee big data analytics as advantage. The issue arises when the pitch is made to a organisation who's existing infrastructure is archaic. Thanks for sharing the useful informaiton.
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  8. The issue arises once the pitch is formed to a organization who's existing infrastructure is archaic and that they have only a few information sources which will be mined. Thus once we say we will monitor of the time supplying.

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