IOT Peaks While Big Data Finds Trough Of Disillusionment.

The Internet of Everything - A new era where everything is connected

Plateau of productivity:

To dive into trending technologies (here IOT and Big Data) that are in hype and to understand when they will become commercially viable, let's take a jab at the Hype Cycle and its Stages. Hype Cycle is a branded graphical tool developed and used by Gartner for representing the maturity, adoption and social application of specific technologies.

Hype Cycle. Source: Gartner.

Hype cycle is mainly classified into five phases: The first phase "Technology Trigger" starts when a potential technology breakthrough occurs and proof-of-concept stories trigger media headlines at this stage early adopters start investigating and normally the products is of no commercial value or use. The second phase is the "Peak of Inflated Expectations" at this stage the mass media goes viral and supplier proliferation begins. A few companies, approx. 5% of audience start working on the pilot implementations, to get a firsthand at the technology, a few of them result in success stories. This third phase is "Trough of Disillusionment", it's time for supplier consolidation and failures, interest fades as experiments and implementations fail to deliver to expectations of the consumer at this stage. The investments will continue to flow in only if the remaining producers work to improve the product quality to the satisfaction of the early adopter. The fourth phase is the "Slope of Enlightenment" more possibilities on how the technology can benefit the enterprise start to become clear and become more widely understood. Second and third generation products appear from technology providers along with support for those products. Methodologies and best practices are developing at this stage. More and more enterprises start funding pilot projects, conservative companies remain conservative ;). In the fifth and final phase of Hype cycle "Plateau of Productivity" there is high growth and increased adoption of the product, 20-30% audience have already adopted the innovation, as a result of the product becomes commercially viable and starts paying off the producers for its product and services. Hype cycle ends when innovations reach the early majority, early majority are one who adopt an innovation after a varied time that is significantly longer than the innovators and early adopters.

Hype Cycle August 2014. Source: Gartner

Big data fame and future:

Big data systems tend to have raw data, like business operations log reports, website user activity tracking, or other real world usages like census surveys. This raw data is left as is because its usage is not predetermined, so there is no known target to transform it to. Most of unstructured/raw data that never had any real value, now is being used by big data systems in making data useful.

Eg: Retailers can now track user web clicks to identify behavioral trends that improve their campaigns, pricing and stock inventory. Governments and even Google can detect and track the emergence of disease outbreaks via social media signals. Take an example of any major bank, they get millions of customer service calls and it has lots of useful information. All of this unstructured call data can now be used by banks to reveal the top reasons for the call and take action to completely eliminate calls for that reason in the future.


 

 
So far, so good. What next. Big Data ruled the "Peak of Inflated Expectations" last year, but now big data has moved down to the "Trough of Disillusionment" replaced by the Internet of Things at the top of the hype cycle. What's intriguing to me is that, interest in big data remains undiminished, yet Gartner gives it a 5-10 year time to reach the "Plateau of Productivity"(Refer to Hype cycle, August 2014), Is Gartner still skeptical? What it means to big data is that it has moved beyond the peak as supplier consolidation has taken place and markets have settled into a reasonable set of approaches, and the new technologies and practices are only additive to existing ones. Only time can tell if investor confidence continues in Big data reaches the "Plateau".


 

IOT Peaks, what's next:

The Internet of Things (IoT) is a scenario in which a set of objects that have a unique identifiers(IPs) and have the ability to transfer data over a network and communicate with each other without requiring human-to-human or human-to-computer interaction. Ever wonder, movies like "I, Robot" and "Terminator" coming to life, a far-far dream, but has definitely begun, not in as Hollywood style though. As per the August 2014 Gartner report on Hype cycle, it will only take 2 to 5 years for IoT to reach the plateau of productivity.  Gartner also say that, "IoT will go on to include about 26 billion units installed by 2020, and by that time, IoT product and service suppliers will generate incremental revenue exceeding $300 billion". With so many devices getting connected to internet and IPv4 being able to address only 4.3 billion addresses, it would have been a problem, now that we have IPv6 and it can address 340 trillion trillion trillion possible IP addresses, in short every atom on the planet can be addressed, that is no more a concern for IoT, right.

A thing, in the IoT, can be a person with a heart monitor implant, cell phones, coffee maker, washing machine, headphone, lamp, wearable devices, or any other natural or man-made object that can be assigned an IP address and provided with the ability to transfer data over a network. So far, the Internet of Things has been most closely associated with machine-to-machine (M2M) communication in manufacturing and power, oil and gas utilities. With the advent of wearable devices, home automation, even the Human to Environment (or also know as H2M) communication with its surroundings is well on its way.

 

 

Eg: Let's take a peek at daily activities and how it might looks like with IOT propagating every aspect of our life. Say you have set up an alarm at 6am in the morning, alarm clock wakes you up at 6 am and then notifies your coffee maker to start brewing coffee for you and the coffee maker will notify your TV to start your favorite news channel, by the time you get ready and close your house door to start to office, the door lock sensors relays signal to your car to start and your car in turn connects with your meeting calendar to choose the best route depending on traffic and your meeting time and still if the traffic is heavy your car will send a text note to the other parties on the calendar invite notifying them that you are running late, the possibilities are endless and achievable now, and more so that they are becoming more and more affordable and commercially viable.


 

References:

http://www.gartner.com/it/content/2760900/2760917/july_15_hypcycleforproviders_hbarnes.pdf?userId=78021830

http://www.forbes.com/sites/gilpress/2014/08/18/its-official-the-internet-of-things-takes-over-big-data-as-the-most-hyped-technology/

http://www.oracle.com/us/technologies/big-data/finding-value-in-big-data-1991047.pdf\

http://www.infoworld.com/d/cloud-computing/the-cloud-and-big-data-are-no-threat-data-warehouses-243801

http://olap.com/forget-big-data-lets-talk-about-all-data/

http://www.forbes.com/sites/jacobmorgan/2014/05/13/simple-explanation-internet-things-that-anyone-can-understand/

http://www.mongodb.com/big-data-explained

http://www.control4.com/blog/2014/03/the-internet-of-things-and-the-connected-home

http://www.businessinsider.com/the-internet-of-everything-2014-slide-deck-sai-2014-2?op=1