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The IoT needs to be distinguished from the Internet. The Internet, of course, represents a globally connected number of network, irrespective of a wired or wireless interconnection. IoT, on the other hand, specifically draws your attention to the ability of a ‘device’ to be tracked or identified within an IP structure according to the original supposition.
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In the age of  Digital Transformation, Artificial Intelligence has come a long way from Siri to driverless cars.
If you have used a GPS on Google Maps to navigate in your car, purchased a book recommended to you by  Amazon or watched a movie suggested to you by Netflix, then you have interacted with  artificial intelligence.
Artificial Intelligence is the capability of a machine to imitate intelligent human behavior which relies on the processing and comparison of vast amounts of data in volumes with help of  big data  analytics, no human being could ever absorb.
Stephen Hawking, Elon Musk, Bill Gates have recently expressed concern in the media about the risks posed by AI.
According to them, AI will soon replace all kinds of manual tasks and make humans redundant. This could be true in some sense but still this is a far cry from the current maturity levels of AI, which is still at the stage of figuring out real-world use cases.
Today machines can carry out complex actions but without a mind or thinking for themselves. Smartphones are smart because they are responding to your specific inputs.
The world’s top tech companies are in a race to build the best AI and capture that massive market, which means the technology will get better fast, and come at us at faster speed. IBM is investing billions in its Watson, Apple improving Siri, Amazon is banking on Alexa;  Google, Facebook and Microsoft are devoting their research labs to AI and robotics.
Together, they will swirl into that roaring  twister, blowing down the industries and businesses in its path.
Within maybe few years, AI will be better than humans at diagnosing medical images and converting speech to emotions. But it can also be stealing millions of records from a government agency to identify targets vulnerable to extortion.
Soon you’ll be able to contact an AI doctor on your smartphone, talk to it about your symptoms, use your camera to show it anything it wants to see and get a diagnosis that tells you to either take a couple of Tylenols or see a specialist.
In all the fairy tales we have seen so far, good almost always wins over evil.
This is what we have seen in the movies like I, Robot or Avengers: Age of Ultron.  But Will Smith or team of avengers does not know that till end of the story. That’s where we are now: face to face with the demon for the first time, doing everything we can to get through the scary plot alive.
Today many companies are using AI for improving their business:
·         Geico is using Watson based  cognitive computing to learn the underwriting guidelines, read the risk submissions, and effectively help underwrite
·         Google Translate applies AI in not only translating words, but in understanding the meaning of sentences to provide a true translation.
·         IBM Watson is the most prominent example of AI based question answering via petabytes of data retrieval that helps in various areas like finance, healthcare & insurance.
As Humans we are programmed from childhood either by nurture or nature to do things the way we do. All the nine emotions we have learned since then are the inseparable part of our lives.
Currently we are in the control of the planet because we are smartest species compared to all the animals.
But when, and if machines learns to love or hate, work in peace or retaliate in anger, then it’s not too far that, with the ability to consume & digest the vast amount of data, they will become more smarter & start taking control of the planet.

Only then we will be able to know that AI is helping us like Iron Man's Jarvis or planning to eradicate us like Terminator!!
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The widespread use of the Internet of Things (IoT) is systematically impacting worldwide growth in online transactions, and research from Gartner underscores that this trend shows no signs of waning.

This compounding growth in connected devices and their use in online transactions has created new challenges for merchants trying to stay compliant with a complex web of global ecommerce regulations that vary by country and state.

As merchants bear the burden of regulatory compliance, they need to be able to quickly adapt to changes to ensure competitive advantage and sustained success.

Take the popular “driver for hire” company Uber. A few years ago in India, Uber’s largest market behind the U.S., the government closed a loophole in a 2009 law. The amended law required two-step authentication (with verification codes sent via text or email) for any “card not present” transaction. In other words, the ease of the Uber app’s payment system was now illegal for the sake of added consumer protection.

This not only put the company at risk of noncompliance in India, but the change could have shut down the company’s operations in India altogether. Even though Uber acted quickly and updated its app, consider the potential negative consequences had it not been able to pivot: heavy fines, potential lawsuits or, even worse, allowing an opportunistic competitor to strategically enter the region. The ability to nimbly pivot when facing unexpected changes is what has, in part, given industry leaders like Uber market dominance.

This past November, the EU introduced legislation banning unjustified geo-blocking between European member states to boost ecommerce across the region.

Geo-blocking is a discriminatory practice preventing customers from making online purchases outside of their resident nation. With the new legislation, a consumer in France, for instance, can purchase goods off a German ecommerce site instead of being re-routed to the French site, where prices may be higher.

This measure was made to promote – rather than restrict – commerce in the EU , forbidding traders from blocking or limiting customer access to their online interface based on nationality or place of residence. And while the new legislation provides a tremendous advantage for the consumer, it forces merchants to adjust how they’d previously done business. Opening up the market, merchants not only lost their price discrimination leverage, but also had to ensure they updated their payment processing and other systems to avoid business disruption and remain compliant. Ultimately, those that are flexible enough to address these requirements will thrive over less nimble competitors.

One thing is certain for merchants: as consumers buy more online, merchants need to prepare for the unexpected. The previous examples just scratch the surface when it comes to adjusting for new ecommerce regulations. Many questions remain unanswered when it comes to commerce and consumer protection, namely: 

  • Will products enabled with automated subscription services (think Tide detergent ordering replenishment pods) have a required notification period before an order is placed?
  • Will a consumer’s electronic signature be required before an order is authorized, as in the Uber example above?
  • Does information that is collected and related to health and wellness, such as fitness tracker/health band data, fall under the protection of additional medical regulations like HIPAA (in the United States)?

How merchants navigate this murky regulatory landscape is critical. Each new regulation can reset the competitive playing field, making flexibility a company’s most important asset.

Companies have every reason to be opportunistic as regulations shift and new opportunities arise. The trick is to put your company in a position to turn the inevitable complexity of global commerce compliance into a competitive advantage – something that may be giving merchants headaches now, but will be well worth the pain once the groundwork has been laid.

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The rise of the Internet of Things was just the beginning. There is something much bigger brewing. It’s called the Internet of Everything — otherwise known as IoE. Instead of the communications between electric-powered, internet-connected devices that the IoT allows, the IoE expands it exponentially. The IoE extends well beyond traditional IoT boundaries to include the countless everyday, disposable items in the world. If the IoT is the solar system, then the IoE is every galaxy in the universe.
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Today we are into  digital age, every business is using  big data and machine learning to effectively target users with messaging in a language they really understand and push offers, deals and ads that appeal to them across a range of channels.
With exponential growth in data from people and &  internet of things, a key to survival is to use machine learning & make that data more meaningful, more relevant to enrich customer experience.
Machine Learning can also wreak havoc on a business if improperly implemented. Before embracing this technology, enterprises should be aware of the ways machine learning can fall flat. Data scientists have to take extreme care while developing these machine learning models so that it generate right insights to be consumed by business.
Here are 5 ways to improve the accuracy & predictive ability of machine learning model and ensure it produces better results.
·       Ensure that you have variety of data that covers almost all the scenarios and not biased to any situation. There was a news in early pokemon go days that it was showing only white neighborhoods. It’s because the creators of the algorithms failed to provide a diverse training set, and didn't spend time in these neighborhoods. Instead of working on a limited data, ask for more data. That will improve the accuracy of the model.
·       Several times the data received has missing values. Data scientists have to treat outliers and missing values properly to increase the accuracy. There are multiple methods to do that – impute mean, median or mode values in case of continuous variables and for categorical variables use a class. For outliers either delete them or perform some transformations.
·       Finding the right variables or features which will have maximum impact on the outcome is one of the key aspect. This will come from better domain knowledge, visualizations. It’s imperative to consider as many relevant variables and potential outcomes as possible prior to deploying a machine learning algorithm.
·        Ensemble models is combining multiple models to improve the accuracy using bagging, boosting. This ensembling can improve the predictive performance more than any single model. Random forests are used many times for ensembling.
·       Re-validate the model at proper time frequency. It is necessary to score the model with new data every day, every week or month based on changes in the data. If required rebuild the models periodically with different techniques to challenge the model present in the production.
There are some more ways but the ones mentioned above are foundational steps to ensure model accuracy.
Machine learning gives the super power in the hands of organization but as mentioned in the Spider Man movie – “With great power comes the great responsibility” so use it properly.
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Have your seen the 1996 movie Twister, based on tornadoes disrupting the neighborhoods? A group of people were shown trying to perfect the devices called Dorothy which has hundreds of sensors to be released in the center of twister so proper data can be collected to create a more advanced warning system and save people.
Today if we apply the same analogy – digital is disrupting every business, if you stand still and don’t adapt you will become digital dinosaur. Everyone wants to get that advance warning of what is coming ahead.
Even if your business is doing strong right now, you will never know who will disrupt you tomorrow.
We have seen these disruption waves and innovations in technologies – mainframe era, mini computers era, personal computers & client-server era and internet era. Then came the 5 thwave of SMAC era comprising Social, 
Mobile, Analytics and Cloud technologies.
Gone are the days when we used to wait for vacations to meet our families and friends by travelling to native place or abroad. Today all of us are interacting with each other on  social media rather than in person on Facebook, Whastapp, Instagram, Snapchat and so on.
Mobile enablement has helped us anytime, anywhere, any device interaction with consumers. We stare at  smarphone screen more than 200 times a day.
Analytics came in to power the  hyper-personalization in each interaction and send relevant offers, communications to customers. The descriptive analytics gave the power to know what is happening to the business right now, while predictive analytics gave the insight of what may happen. Going further  prescriptive analytics gave the foresight of what actions to be taken to make things happens.
Cloud gave organizations the ability to quickly scale up at lower cost as the computing requirements grow with secure private clouds.
Today we are in the 6 thwave of disruption beyond SMAC era - into  Digital Transformation, bringing Big Data, Internet of things, APIs, Microservices, Robotics, 3d printing, augmented reality/virtual reality, wearables, drones, beacons and blockchain.
Big Data allows to store all the tons of data generated in the universe to be used further for competitive edge.
Internet of Things allows machines, computers, smart devices communicate with each other and help us carry out various tasks remotely.
APIs are getting lot of attention as they are easy, lightweight, can be plugged into virtually any system and highly customizable to ensure data flows between disparate systems.
Microservices are independently developed & deployable, small, modular services. 
Robotics is bringing the wave of intelligent automation with help of cognitive computing.
3D printing or additive manufacturing is taking the several industries like medical, military, engineering & manufacturing by storm.
Augmented reality /  virtual reality is changing the travel, real estate and education.
Wearables such as smart watches, health trackers, Google Glass can help real time updates,  ensure better health & enable hands-free process optimization in areas like item picking in a warehouse.
Drones have come out of military zone and available for common use. Amazon, Dominos are using it for delivery while Insurance & Agriculture are using it for aerial surveys.
Beacons are revolutionizing the customer experience with in-store analytics, proximity marketing, indoor navigation and contact less payments.
The new kid on the block is  blockchain where finance industry is all set to take advantage of this technology.
As products and services are getting more digitized, traditional business processes, business models and even business are getting disrupted.
The only way to survive this twister is to get closer to your customers by offering a radically different way of doing business that’s faster, simpler and cheaper.
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Smart IoT - Generate Greatest Value

Digital Transformation

We have now entered an era with a new virtual revolution, particularly, the Internet of things (IoT). The virtual revolution marks the starting of information age. We use the Internet almost every day. The net has turned out to be one of established ways for us to work together, to share our lives with others, to shop, to teach, to research, and to learn. However  the next wave of the Internet isn't about people. it's far about things, honestly?

All about IoT

IoT is defined as the network of physical objects that can be accessed through the Internet. These objects contain embedded various technology to interact with internal states or the external environment.

IoT is characterized as "the figuring frameworks of sensors and actuators associated by systems, where the processing frameworks can screen or deal with the status and actions of connected objects and machines, and the connected sensors can likewise screen the characteristic world, individuals, and creatures." The center of IoT is not just about interfacing things to the Internet. It is about how to generate and use the big data from the things to make new values for individuals, and about how we empower new trades of significant worth between them. In other words, when objects can sense and communicate, IoT has its knowledge to change how and where choices are made, and who makes them, and to pick up a superior esteem, solution or service.

Smart IoT

Fundamental to the estimation of IoT is in actuality the Internet of smart things (smart IoT). Supported by intelligent optimization, smart IoT can increase productivity of work and enhance quality of lives for people. Let us take “cities” — the engines of global economic growth — as an example. Smart cities have the potential to dramatically improve the lives of everyone. In intelligent transportation systems (ITS), smart IoT can not only monitor the status of the transportation, but also optimize traffic signal controls to solve traffic congestion and provide the travelers with better routes and appropriate transportation information, etc. Combining IoT and machine learning (ML) can also make our roads safer. Profits by smart IoT have been shown also in health-care, logistics, environment, smart home, in the aspects of better quality, energy conservation, efficiency increase, and so on.

Smart IoT remains in its infancy now in terms of the technology  development and the effect on our global economy system and our daily lives. Maximum IoT statistics aren't used presently within the era of big data. Maximum IoT has no intelligence inside the generation of artificial intelligence (AI).  IoT which might be used these days are on the whole for anomaly detection and control, as opposed to optimization and prediction. Given the brilliant anticipated increase of the Internet over the following 10 years, it is considered one of vital challenges and possibilities for us to invent and practice in real-global programs on a way to make the IoT smarter to generate the greatest value.

 

 

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A to Z of Analytics

Analytics has taken world by storm & It it the powerhouse for all the digital transformation happening in every industry.

Today everybody is generating tons of data – we as consumers leaving digital footprints on social media, IoT generating millions of records from sensors,  Mobile phones are used from morning till we sleep. All these variety of data formats are stored in  Big Data platform. But only storing this data is not going to take us anywhere unless analytics is applied on it. Hence it is extremely important to close the loop with Analytics insights.
Here is my version of A to Z for Analytics:
Artificial Intelligence: AI is the capability of a machine to imitate intelligent human behavior. BMW, Tesla, Google are using AI for self-driving cars. AI should be used to solve real world tough problems like climate modeling to disease analysis and betterment of humanity.
Boosting and Bagging: it is the technique used to generate more accurate models by ensembling multiple models together
Crisp-DM: is the cross industry standard process for data mining.  It was developed by a consortium of companies like SPSS, Teradata, Daimler and NCR Corporation in 1997 to bring the order in developing analytics models. Major 6 steps involved are business understanding, data understanding, data preparation, modeling, evaluation and deployment.
Data preparation: In analytics deployments more than 60% time is spent on data preparation. As a normal rule is garbage in garbage out. Hence it is important to cleanse and normalize the data and make it available for consumption by model.
Ensembling: is the technique of combining two or more algorithms to get more robust predictions. It is like combining all the marks we obtain in exams to arrive at final overall score. Random Forest is one such example combining multiple decision trees.
Feature selection: Simply put this means selecting only those feature or variables from the data which really makes sense and remove non relevant variables. This uplifts the model accuracy.
Gini Coefficient: it is used to measure the predictive power of the model typically used in credit scoring tools to find out who will repay and who will default on a loan.
Histogram: This is a graphical representation of the distribution of a set of numeric data, usually a vertical bar graph used for exploratory analytics and data preparation step.
Independent Variable: is the variable that is changed or controlled in a scientific experiment to test the effects on the dependent variable like effect of increasing the price on Sales.
Jubatus: This is online Machine Learning Library covering Classification, Regression, Recommendation (Nearest Neighbor Search), Graph Mining, Anomaly Detection, Clustering
KNN: K nearest neighbor algorithm in  Machine Learning used for classification problems based on distance or similarity between data points.
Lift Chart: These are widely used in campaign targeting problems, to determine which decile can we target customers for a specific campaign. Also, it tells you how much response you can expect from the new target base.
Model: There are more than 50+ modeling techniques like regressions, decision trees, SVM, GLM, Neural networks etc present in any technology platform like SAS Enterprise miner, IBM SPSS or R. They are broadly categorized under supervised and unsupervised methods into classification, clustering, association rules.
Neural Networks: These are typically organized in layers made up by nodes and mimic the learning like brain does. Today  Deep Learning is emerging field based on deep neural networks.
 
Optimization: It the Use of simulations techniques to identify scenarios which will produce best results within available constraints e.g. Sale price optimization, identifying optimal Inventory for maximum fulfillment & avoid stock outs
PMML: this is xml base file format developed by data mining group to transfer models between various technology platforms and it stands for predictive model markup language.
Quartile: It is dividing the sorted output of model into 4 groups for further action.
R: Today every university and even corporates are using R for statistical model building. It is freely available and there are licensed versions like Microsoft R. more than 7000 packages are now available at disposal to data scientists.
Sentiment Analytics: Is the process of determining whether an information or service provided by business leads to positive, negative or neutral human feelings or opinions. All the consumer product companies are measuring the sentiments 24/7 and adjusting there marketing strategies.
Text Analytics: It is used to discover & extract meaningful patterns and relationships from the text collection from social media site such as Facebook, Twitter, Linked-in, Blogs, Call center scripts.
Unsupervised Learning: These are algorithms where there is only input data and expected to find some patterns. Clustering & Association algorithms like k-menas & apriori are best examples.
Visualization: It is the method of enhanced exploratory data analysis & showing output of modeling results with highly interactive statistical graphics. Any model output has to be presented to senior management in most compelling way. Tableau, Qlikview, Spotfire are leading visualization tools.
What-If analysis: It is the method to simulate various business scenarios questions like what if we increased our marketing budget by 20%, what will be impact on sales? Monte Carlo simulation is very popular.
What do think should come for X, Y, Z?
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Remember when you were teenager and wanted to go on vacation with parents-you were asked to go to travel agent and get all the printed brochures of exotic locations?  
Then came the dot.com wave and online booking sites like Expedia, Travelocity, Makemytrip paved so much that took travel agencies out of equation.
We used to send holiday postcards to our friends and families back home, which are gone out of business due to  social media postings on Facebook, Instagram.
Lonely Planet used to be the traveler’s bible, but now we go to tons of websites like TripAdvisor, Priceline which provide us with advice and reviews on hotels, tours and restaurants.
Now I am able to book my flight online, have my boarding pass on my phone, check in with machines, go through automated clearance gates and even validate my boarding pass to board the plane
The travel industry, like many others, is being disrupted by great ideas powered by  digital technology and innovation.
Some of the digital innovations travel industry taken so far:
·     Online booking sites like Expedia, Travelocity, MakeMyTrip, Trivago
·     Mobile optimization with Wi-Fi enablement
·     Targeting and  hyper-personalization with Big Data Analytics
·     Digital discounts on travel by Kayak, Tripadvisor
·      Smartphones for research vacations, deals, feedbacks
·      Wearables like Disney band for payments, room keys
·     Bluetooth  beacons to guide travelers in the vicinity at airports
·      Virtual reality – see the places without even getting out of home
All such digital footprint of customers are collected and then analyzed by  big data analytics to hyper personalized the experience.
With extensively networked digital properties and deep hooks into customer data collected via travel booking sites and social media channels, travel companies are delivering customized dream vacations according to the likes and preferences of today’s travelers.
Today’s trend is towards spending money on memories & experiences instead of material possessions.
Accordingly, travel companies are investing in their digital storefronts and  omni-channels to keep today’s hyper-connected travelers snapping, sharing, researching and reviewing on the fly – leaving immense data footprints for marketers to leverage.
Bluesmart is a high-quality carry-on suitcase that you can control from your phone. From the app you can lock and unlock it, weigh it, track its location, be notified if you are leaving it behind and find out more about your travel habits.
Thomas Cook have introduced virtual reality experiences across select stores.
Digital disrupters like Airbnb have already put tremendous pressure on hotels.
Starwood Hotels have launched “Let’s chat”, enabling guests to communicate with its front desk associates via WhatsApp, Blackberry messenger or iPhone before or during their stay.
World has gone from Bullock Cart to Hyperloop today. The future will belong to those using data-based intelligence to offer better experiences, encourage exotic longer and more frequent stays, and build long-term loyalty
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Digital Transformation in Manufacturing

Manufacturing companies have traditionally been slow to react to the advent of digital technologies like intelligent  robotsdrones, sensor technology, artificial intelligence, nanotechnology & 3d Printing.
Industry 4.0 has changed manufacturing. At a high-level, Industry 4.0 represents the vision of the interconnected factory where all equipment is online, and in some way, is also intelligent and capable of making its own decisions.
The explosion in  connected devices and platforms, abundance of data from field devices and rapidly changing technology landscape has made it imperative for companies to quickly adapt their products and services and move from physical world to a digital world.
Today, Manufacturing is transforming from mass production to the one characterized by mass customization. Not only must the right products be delivered to the right person for the right price, the process of how products are designed and delivered must now be at a level of sophistication.
First step in digitization is to analyze current state of all systems starting R&D, procurement, production, warehousing, logistics, marketing, sales & service.
The  digitization of manufacturing impacts every aspect of operations and the supply chain. It starts with equipment design, and continues through product design, production process improvement and, ultimately, monitoring and improving the end-user experience.
Digital transformation revolutionizes the way manufacturers share and manage product & engineering design, specs on the cloud by collaborating across geographies.
Down time and reliability are critical when it comes to the operation of equipment and machines on a shop floor. With  Big data Analytics, the quick and easy access to this operation data, production information, inventory, quality data gives ability to quickly adjust to machine status across the enterprise.
Quality and yield is directly related to manufacturing processes as to how raw materials are used, inspected, manufactured, and how everything comes together. This really determines the quality level of the products.  Cognitive computing enables earlier identification of nascent quality problems, increased production yield, and reduction of problems that lead to service and warranty costs.
Implementing  smarter resource and supply chain optimization strategies helps to improve the cost efficiency of these resources like energy consumption, worker safety, and employee resource efficiency.
Service Excellence is also an important part of the strategy that companies are using to achieve digital transformation in the manufacturing space. Connected Devices ( IoT) are changing the paradigm of delivering after-sales service. Some of the advantage are most prevalent in several selected industries, such as industrial equipment, power generation and HVAC providers:
·       Push Service Notifications
      o   How is your asset health?
      o   How is your asset usage?
·       Predictive/  PreventiveMaintenance
·       Break-Down Assistance
·       Usage-based Billing
·       Spares Fulfillment
General Electric’s jet engines combine cloud-based services, analytics and on-line sensors to report usage and status and help predict potential failures. The result is improved uptime and lower cost of ownership.
Additive manufacturing (3D printers) for prototyping help shorten the iteration cycles in the design process and help to turn innovation into value. 3D printing is also quickly gaining ground in the commercial manufacturing of customized products in low volumes.
Smart machines integrated with forklifts, storage shelves and production equipment. These machines are able to tak
e autonomous decisions and communicate with each other to drive material 

replenishment, trigger manufacturing and much more.
Industry 4.0, allowing manufacturers to have more flexible manufacturing processes that can better react to customer demands.

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What is the difference between UX & UI?

Remember when we were young and wanted to use ketchup and it did not fall down from the glass bottle in the dish? We had to turn the bottle upside down and smack it on the bottom to pour it. The company did not realize that making the glass bottle with attractive label looks good but actual experience of using it is very bad. 
That is the simple difference between user interface (the glass bottle) and user experience (pouring the ketchup).
A User interface is a simple, intuitive means for a user to interact with PCs,  smart mobile devices, websites, communication devices, and software applications.
All our five senses Sight, Sound, Smell, Touch and Taste are user interface for us to interact with the world and what we get is user experience of the world.
Today with so much digital all around us, User interface (UI) focuses on the look and feel of screens, pages, forms, text boxes, and visual elements, like images, videos, buttons and icons that you use to interact with a device, web site or product.
User experience (UX), on the other hand, is the experience that a person has as they use, interact with products and services.
Imagine when you ask a query to Google and it took more than 1 minutes to get a result. Even if the interface stayed the same, your experience with Google would be dramatically different.
UI will more focus on look and feel, responsiveness of the product. It cares for if the function works or not. UX design not only cares for its function but the users' emotion, how the users feel about when their interaction to UI.
Positive User experience enhances customer satisfaction and loyalty by improving the usability, ease of use, and pleasure provided in the interaction between the customer and the product. 
UI is when you go to a five star hotel for dinner and see food arranged beautifully and UX is when you eat it to find it fantastic too.
You must have visited Disneyland with your kids….the attractive colors, and themes they use to pull the crowds of children and adults at same time is user interface while after sitting on the rides like space mountain, rock n roller coaster, free fall etc. what you get is thrilling user experience.
Your Car’s steering wheel, brakes, accelerator are all UI, while kind of experience you get driving is UX.
Your UI design can make or break the success of your website or app and it is the door to the great or worst user experience.
There are some basic principles for UI to be successful:
·       Make UI as intuitive &  responsive as possible
·       Don’t overload the information
·       Keep it simple to view
·       Group things appropriately
·       Multi language support with proper tool tips
Something that looks great but difficult to use and something that looks terrible but very easy to use, both are failures in today’s  digitalage.
UX and UI are the two most integral concepts in the world of website development. Both need to work well in relation to each other to offer the best overall outcome.
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A few weeks ago, when I returned from the MWC and I wrote about “The wandering souls Network”, I wondered if it would not have been better for my career if I had specialized in a very specific area instead of being a generalist. I think there are decisions in our life that in spite every of us can analyse many times, the final decision will be always the same, because each person is the way he is.

“I define myself today as “A Generalist specialized in Internet of Things (IoT)”

Although the rest of this article can possibly be applied to all White Collar professionals, I'm going to focus on how will affect your decision of being an IoT specialist or an IoT generalist in a futuristic world dominate maybe by Robots.

Defining IoT Generalist and IoT Specialist

Before start examining the pros and cons of becoming an IoT generalist or a IoT specialist in this competitive and unfair world, it’s important to understand the distinction of these two approaches and how they relate to our future career path.

The Merriam-Webster dictionary’s simple definition of a generalist states a generalist is “a person who knows something about a lot of subjects”. A specialist is defined as “a person who has special knowledge and skill relating to a particular job, area of study”.

An IoT Generalist is a professional that understand a bit of everything. The IoT Generalist can speak about new business models enabled by IoT, the value of ecosystems, all kind of networks connectivity, protocols, sensors, devices, Gateways, Architecture, Cloud Platforms, Edge Analytics or Predictive Maintenance. And of course, he must be up to date of standards and security. Such a professional should be able to present to C-Level but also to maintain an intelligent conversation with different technical people. A value added of an IoT Generalist is his/her social network reputation, industry expertise recognition and strategic relationship with IoT/IIOT vendors, Telcos, Analyst, System Integrators. 

Being an IoT generalist also require a skill-set of project management, effective communication and good people skills.

Do you have anyone in mind?

An IoT Specialist is a professional that is a subject matter expert in at least one of the core IoT tracks. Since the IoT is very complex even though we try to simplify it with concepts such as  IoT in a Box, an IoT Specialist should offer at least expertise in one of the following 6 distinct tracks:

  • IoT Devices (IoT Hardware Engineer or IoT SW Embedded Engineer)
  • IoT Connectivity (5G, LTE, NB-IOT, 3GLoRA, SigFox, WiFI, Bluetooth) (IoT Telco Engineer)
  • IoT Platforms (IoT Architects)
  • IoT Edge/Cloud Analytics (IoT Data Scientists)
  • IoT Enterprise Integration (IoT Business Process)
  • IoT Development and DevOps. Take a look “IoT Skills For Developers”

Do you have anyone in mind?

But possibly to survive the future era of robots, it may matter little to be an IoT Generalist or Specialist and you will need a mix of a (someone who starts out as a generalist, but also has in-depth knowledge over a particular area) or specializing-generalist (someone who is specialized in a particular field, but also has a broader understanding of other aspects of the business) as Lev Kaye, the founder and CEO of CredSpark, wrote.

Remember that moving between both extremes can be extremely difficult once a career path has been embarked upon, so the mix is always good to have. There is, of course, opportunity to move between general and special IoT roles. But the more experience a professional gain in one area or the other, the more difficult it becomes to make a transition, at least without suffering from a dramatic salary loss.

Advantages and Disadvantages of being an IoT Generalists vs an IoT Specialist

There are benefits and downsides to both career routes. In the following table I have included some upsides and downsides of becoming an IoT generalist versus becoming an IoT specialist.

 

IoT Generalist

IoT Specialist

Advantages

  • Having a good understanding of a wider selection of IoT topics can help make better decisions and find solutions that a specialist might not be able to see.
  • In a fast-changing workplace, IoT generalist transferable skills will become increasingly important and will be less restricted with their career opportunities.
  • The salaries tend to be higher, even at the starting point and can also provide more internal power.
  • You can become a widely recognized leader in your field.

 

Disadvantages

  • By simply knowing the surface you can easily be replaced by another generalist.
  • Become a widely recognized leader will require specialization.
  • The narrowed focus and expert skills in an area mean IoT Specialist can only find work in this narrow field.
  • ·   The opinion on other issues might not be as valid if the topic at hand not involve your area of expertise directly.

 

“The good news is that IoT job market is likely going to require both”

Age does matter - Which path is right for you?

If you are at the start of your career, you are probably pondering which route you should take: IoT Generalist or IoT Specialist

When you start, selling yourself as an IoT generalist could be complicate to justify in a job interview, so will be better become a subject matter expert and then progressively move into a specializing-generalist

My Opinion: If you are under 30 you need to stay on top of your areas of IoT expertise and be willing to move when your expertise becomes a commodity or obsolete. This requires vigilance and the willingness to move with industry trends. You must be aware of disruptive trends in IoT technologies. Take into account that in the future, the IoT Specialists will be also under threat from software and robots. 

But if you have already passed the barrier of 45 years and suddenly you want to use your background and experience to sell yourself as an IoT Generalist, remember that you have 6 months to demonstrate your added value (most of the time you will be required for selling) or you will be fired without any leniency.

My Opinion: As an IoT Generalist over 45 you will find harder and harder to get hired. You need to be creative and become at least in spirit an entrepreneur. You must continue creating your own brand and reputation and extending your network with key people in the industry. Opportunities for IoT Generalist will not be forever but they must fight project by project. It would not hurt to start specializing in any of the IoT tracks.

And Enterprise size matters too. What are you looking for?

IoT Startups

Governments insist to sell us the importance of entrepreneurs for the well-being and sustainable development of countries and encourage us to create startups. Of course, there is no work for life except for Government employees. And it is known that the big multinationals are rewarded in stock market by the number of employees that are fired out each quarter.

Even so, startups are possibly the only way out for IoT Specialist under 25 or IoT Generalist over 45.

My Opinion

  • ·         If you are an IoT Generalist over 45, find a job in IoT startups will be a chimera, except as Sales roles. Launching your own startup with other partners can be a better option.
  • ·         If you are an IoT Specialist under 25 you can try to convince other colleagues to create a Startup and enter in the dynamic of find investors, win awards and pray for a stroke of luck. If you decide to work in an existing startup to get experience and you are not a Founder or Co-Founder, you must be prepared to be exploited, and then move to a Big company.

SMB (Small and Medium Enterprises)

IoT Generalists add value specially to medium to big international companies. Knowing the details about the complex ecosystem and can handle a vast array of technical concerns is becoming critical for SMBs. There is little need for IoT specialist as there are not enough technical needs in any one specific area to warrant a full-time staff member dedicating themselves to them.

This does not mean that if you are an IoT Specialist you should not try to work for a SMB. Other consideration like industry knowledge, proximity or quality of life will compensate the promises of more money and relevance in Big International companies.

My Opinion:

  • ·         IoT Generalist over 45 are typically more valued in smaller organizations. Small organizations typically cannot afford to hire a lot of IoT specialists. You will be more valued in smaller organizations who need their employees to wear a lot of hats. In a SMB the transition to a generalizing-specialist will be natural-
  • ·         If you are an IoT Specialist under 25 and you do not pursue the fame of being a number in a Big international company, you can enjoy more in a SMB because you will have more probability to become more quickly a specializing-generalist.

Big International companies / Top IoT companies

Here we must separate into two types of companies: Top IoT companies including Big IT and OT vendors and End Customers.

There are many lists of Top IoT companies. Almost always these lists include the habitual suspects, and as usual they have notable absences and without forget that the ranks leave much to be desired. But at least such type of list provide the names of companies that either IoT Specialists of IoT Generalists should be searching for a job.

End Customer will need help from both IoT Generalist and IoT Specialist, the question is when and who are them?

My Opinion:

  • ·         The desire of an IoT Generalist over 45, that used to work on Big Companies, is return to a Top IoT Company or Big Enterprise. Although it would seem easy, it is by no means a road of roses. You must create your own strong personal brand and be a well-known and influencer of the industry.
  • ·         If you are an IoT Specialist under 25 with experience in startups you will be hunted soon for one of IoT Top vendor.  Do not let yourself be blinded by the name of the company, but the project and the future importance of IoT within it.

Looking beyond 2025, the begin of the era of robots

Not because I attend the MWC that specifically caused me to think back on the changes that will occur in the IoT job landscape, it was this conference in addition to the many other IoT events that I attended over the past years that make me think how IoT professionals will be living the strong gravitational rift as we approach to 2025 and beyond.

Unemployment is one of the main problems in today consumer owned society. The unemployment is especially cruel to young people in search of their first job. But also for those who have passed the barrier of 45 (IF $your age is >45 THEN "sorry you are overqualified”).

When I wrote “Your job will be in our special metal hands” I imagined a near future in which companies will use Recruitment Robots to search, identify, select and manage candidates and employees more efficiently. Although it is crucial you follow your heart and your passion when making the decision you should consider the requirements of future employers will be robots.

If today, what matters is knowing a little of everything in the Internet of Things, an IoT Generalist, cross-trained and energetic. Fast forward a few years, and the IoT profession will took a different turn. IoT Specialists must emerge, particularly in larger organizations.  IoT Specialist should also be aware of the way IoT jobs will change. Several traditional IoT specialist jobs today will be facing the threat of automatization and will not have an easy time beyond 2025.

THE BOTTOM LINE

When deciding between IoT generalist and IoT specialist career paths, you need to carefully consider the type of person you are. Ultimately, the advantages and disadvantages of either path depend on your personality and drive. If you work hard towards achieving your career goals, you can do so as an IoT specialist and as an IoT generalist and remember you need to be passionate and your attitude will matter today and beyond 2025.

IoT Specialist or IoT Generalist? Choose your own destiny.

Thanks for your Comments and Likes

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Many organizations today have realized that  digital transformation is essential to their success.
But many of them forget that focus of a digital transformation is not digitization or even technology, it is the  Customer!
Digital Transformation is not easy or small endeavor for any business. Several levers will need to be turned in unison just to ensure resources are aligned and budgets are not being wasted.
Many a times I have seen that the top boss is not digital savvy. In such cases without top leadership, they are unlikely to have real impact on their road to digital.
Another reason is, many companies focus on siloed, just few digital projects instead of overall business model transformation. Such independent, tactical initiatives, which are costly and create bad publicity inside and outside the organization.
I had a worst experience with one of the largest telecom company. While acquiring customers they go out the way to give everything free and promise everything digital. But their customer service is pathetic. I just wanted to disconnect my internet dongle and it was not possible online. I had to call customer service 5-6 times, every time I was kept on hold saying they are checking system status.  At one time, when I got frustrated I asked why it is painful just to disconnect, the rep told me sir your call has just consumed 39 seconds and we are trained to hold customer for more than a minute!!! See how they earn money at customer’s cost.
Finally they told me go and sort it out in one of their store. Again no digital there – I had to fill out a hard copy form, provide all my id proofs again, and I was told it will take 10 more days to just disconnect the service, so I have to pay for those 10 days.  What is worst is, I again get a bill after 1 month that I have not paid latest bill.
From the telecom’s perspective, they think they have done everything right for digital transformation:
1. They have provided online access to manage account; 
2. They have a sleek mobile app
3. They have provided access to a 24x7 customer support line
4. Their web site UX and design gives good online experience
5. They provide email updates letting customers know the status on their requests.
But if they had walked in customer’s shoes, to identify instances where things could do wrong and address them quickly, it would have been more successful.
If with everything at the end the  customer experience is bad it is a failure.
Lack of clear vision - Often times, companies that are not succeeding simply haven't painted a clear picture of what they want or need to be, when they digitally "grow up."
Poor internal communication within employees is another critical reason to fail. All the customer touch points don’t communicate with each other to have single version of customer truth. A comprehensive use of  Big Data Analytics is essential to have all the details of customer at service rep’s fingertips.
Amazon, Netflix and Uber digital success stories have the effective gathering, storing and leveraging of customer data at the core.
Forrester has cited example of digital transformation failure at BBC for weak project management, reporting, lack of focus on business change.
Which reasons resonate with you? Happy to hear your thoughts!
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The Internet of Things (IoT) is a technology that extends digital connectivity to devices and sensors in homes, businesses, vehicles and potentially almost anywhere. This advance enables virtually any device to transmit its data, to which analytics can then be applied to facilitate monitoring and a range of operational functions. IoT can deliver value in several ways. It can provide organizations with more complete data about their operations, which helps them improve efficiencies and so reduce costs. It also can deliver a competitive advantage by enabling them to reduce the elapsed time between an event occurring and operational responses, actions taken or decisions made in response to it.

IoT utilizes what Ventana Research calls operational intelligence, a discipline that has evolved from the capture and analysis of data from instrumentation and machine-to-machine interactions of many types. We define operational intelligence as a set of event-centered information and analysis processes operating across an organization that deliver information to enable effective actions and optimal decisions.

The evolution of operational intelligence and its manifestation in IoT is encouraging companies to revisit their priorities and spending for information and other digital technologies. Ventana Research undertook benchmark research on The Internet of Things to determine the attitudes, requirements and future plans of organizations that use IoT and operational intelligence systems and to identify their best practices. We set out to examine both the commonalities and the qualities specific to major industry sectors and across sizes of organizations. We considered how organizations manage IoT, issues they encounter in the process and how their use of it and related technology is evolving.

While the Internet of Things may still be a novelty to many consumers, organizations participating in our research are well aware of its applications and implications. Four out of five (81%) said IoT is important to their future operations. Majorities said the use of IoT is very important to speed the flow of information and improve the responsiveness of individuals within business processes (61%) and to speed the flow of information to customers or consumers (58%).

The most common uses of IoT are associated with customers (as in sensors on products, by 43%), employees (in wearable technology, 35%) and sensors on devices in the supply chain (31%). At this point, however, more organizations are able to capture IT events (such as a network or system security breach, 59%) than business events (such as a customer contact, 45%). As organizations find more business uses, IoT and operational intelligence will become even more mainstream, and the research indicates that this will occur. Within two years, 95 percent of organizations said they expect to be capturing IT events and 92 percent to be capturing business events.

The research also finds that the intentions of organizations to embrace IoT and use operational intelligence often outpace their current capabilities. For example, many can capture data but face challenges in using it. More than two-thirds (68%) said they are satisfied or somewhat satisfied with their organization’s ability to capture and correlate data from events. After that, managing and using it become more complicated. Nearly one-third (31% each) reported difficulties with inadequate data or in managing external data. About half (48%) said they spend the most time reviewing event data for quality and consistency issues, which suggests a lack of standardization across the data sources that are collected.

Furthermore, most organizations are not ready to derive maximum value from IoT. The processes most commonly implemented, each by approximately half of organizations, are performing root-cause analysis, defining measurements and metrics, and monitoring and correlating activities or events. While these processes are necessary, they are only the first step in improving performance. Fewer have advanced to the point of automating processes, which will be necessary to make full use of the coming deluge of IoT data. For example, only about two in five use data from events to trigger automated processes such as predictive maintenance (38%) or automatic assignment of thresholds for alerts (39%).

This research overall finds strong momentum behind the emergence of the Internet of Things, but it also is clear that many organizations have not caught up to the trend. IoT is here, and its impact on business will only increase; almost all companies can benefit from paying attention to it. We encourage you to use this research to help educate and guide your organization through its IoT journey.


Regards,

David Menninger

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With  Digital Transformation, we are living in direct-to-customer world. 
Consumers don’t want to talk to middlemen or brokers when they need something. They also don’t want to be bombarded with irrelevant ads, nor do they want to be on the receiving end of a blanket, irrelevant marketing campaign.
Customer expectations are high, and growing! To provide a differentiating  customer experience, you must exceed, or at least meet their expectations.
Almost anything you read today talks about customer engagement and customer experience. It’s not because those are the latest buzzwords, it’s because they really affects your top line. 
It is also a compliance matter now a days to know your customers well.
Customer simple expectations are Know Me, Understand me, Respect me, Listen to me, and Respond to me anytime, anyplace.
Modern customers demand intelligence from the organizations they engage with. They demand knowledge, care, and tailored content and campaigns.
Digital technology has turned customers into moving targets. Customers are hopping the channels all the day – start with smartphone, tablet at the breakfast, continuing on mobile while commuting to work, then hoping to laptop/pc in office, and again moving to other devices when out of office and then TV, tablet, mobile at home before finishing the day. This leaves huge digital footprint for businesses to further analyze.
Today, customer data, knowledge, and insights are more valuable and of more strategic importance than ever before
Business have to adopt to various key elements to engage customers:
·  Involve customers: allow customers to engage and involve in your business goals
·  Anywhere anytime Access: give them flexibility to connect to your business from anywhere, on any device, anytime
·  Relevant content to Engage: provide the content which makes sense to customers
·  Hyper personalize: customize the content to the very personal level meeting specific needs
·  Responsiveness: quick and effective response on customer interaction
Businesses can deploy  big data analytics to bring in all the advanced customer intelligence while interacting with customers:
·   Customer journey data: Collecting all the customer data across all the touch points of your business
·  Behavior data: How customers have behaved while interacting with your business
·  Sentiments data: What customers are saying about your products and services – good or bad
This helps in Knowing the customers better than the competition does, not only knowing who they are and what they have purchased, but also understanding what they want at a particular moment in time.
Amazon, Disney, Apple, Starbucks go to great lengths to exceed customer expectations by leveraging customer information and insights.
Finally knowing the customer helps you in marketing, advertising, customer service, customer retention and loyalty and above all improve the customer experience.
Knowing your customer is key to survive. Find out who they are and how you can create products that truly solve their needs

How is your organization putting efforts to know your customers in digital age?

Originally published at  here.
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First of all, I will explain the reason for the post title. For those who have not seen the films, I summarize: "A group of four illusionists win year after year to the public with their incredible magic shows and even mocking the FBI.

GSMA is a great illusionist and MWC is their principal magic show. We are invited year after year to visit an event with unique keynote speakers, an enormous list of exhibitors, amazing performances and a great LinkedInplace where we can meet in person some of our social media contacts. What else can we ask for?

I know that it is very ruthless to compare the GSMA with illusionists and the MWC as their greatest magic show, but at least I see quite a few reasonable resemblances, you don´t.

 My fears and my wishes for MWC17

If in 2015 I wrote " MWC 2015: Everything Connected, Tapas and Jamon", and I argued as one the reasons to attend MWC was the fact it was celebrated in Barcelona. In 2016, in my post “GSMA need to think how to reinvent MWC” I justify the reasons why the MWC needed to reinvent itself.

One thing has become clear to me after many years attending MWCs, this is the world's biggest phone and mobile networks show, with manufacturers set to unveil a raft of new phone handsets and new technology. However, the GSMA had insisted on introducing more and more distractions like Internet of Things (IoT), Connected Living, Connected Car, AR/ VR, Robots. Maybe the reason is because Telecom operators do not have the DNA to change. Still, many telecom operators take a dim view of some of the aggressive moves being made by these peers, especially when it comes to business models based on commercializing customer data.

“I expected to see less hype and a dose of common sense”

 Starting by the announcement of Spain’s Telefonica to introduce a broad plan “4th Platform” to help both consumer and business customers keep greater control over their data rather than giving it away to web giants Google, Facebook and Amazon.

 “I expected to see more applications where IoT will become a lot less exciting, but more useful and profitable. The real world.” 

But I also feel like Scott Bicheno that  “Mobile World Congress is disconnected from reality”.

 

The Top 5 tricks of illusionism this year

5G, Network Slicing and their associated Business Models

5G will undoubtedly be the next big thing in mobile wireless networks. For Niall Norton: fact, fiction, MWC – and strangers dancing in the dark, the most over-hyped technology or trend this year will be 5G in spite he thinks 5G is still miles away and therefore we have to wait for augmented reality, virtual reality, driverless cars and the like. It is a big ask for investors to keep piling money in.

For Phil Laidler, Network slicing is essentially an extension of policy control, virtualisation, NFV and SDN, and their orchestration; the move towards software-centric, flexible end-to-end networks. At MWC this year he is looking forward to seeing more "proof of concepts" for network-slicing and the associated business models, in addition to any insights into how slicing will work in practice.

Nokia’s big 5G announcement on ‘day 0’ of the event was overshadowed by a large consortium of operators and vendors calling for just the ‘new radio’ part of the 5G standard to be accelerated, despite the fact that it will lack the backhaul, cloud infrastructure, software platforms, etc needed to make the 5G dream viable. If anything highlights the wishful-thinking folly of much of the talk at this year’s show it’s that.

IoT

IoT has been a hot topic at MWC for the last few years, but, operators do not succeed with new business models beyond managed connectivity. Strategic alliances with IoT vendors has shown no results yet.

The battle between connectivity technologies remains fierce, cellular IoT Chip Battle Escalates at MWC ARM, Sequans and Altair to compete on NB-IoT solutions, but vendors and operators are now looking for more innovative ways to overcome the problem. This might just be the year of Low-Power Wide Area Networks (LPWAN).  Although LoRa and Sigfox are currently dominant in the LPWA market, cellular IoT proponents had steal the show.

For example, Telefonica - who is working on NB-IoT with Huawei - recently announced a global partnership with Sigfox. In addition, Nokia launched its worldwide IoT network grid ('WING') a few weeks ago, which it describes as "a 'one-stop-shop', full service model offering seamless IoT connectivity across technologies and geographical borders."

For Operators, the real value from IoT will be created when they can start combining data sets from different areas and different connectivity technologies. For example, smart cities, healthcare or Food & Beverage, retail, transportation and logistics to improve the cold chain supply management processes.

I hope that at MWC18 we will be looking out for examples of operators and vendors developing IoT use-cases that do just that.

“The Internet of Things is in MWC to stay for a few more years, but If your focus is Internet of Things (IoT) then your money probably will have more ROI in other IoT events”

Blockchain

Blockchain has become one of the latest buzz words in telecoms, IT and IoT , thanks to a rapid increase in start-ups using it for new use-cases beyond its original application in financial services. Despite the excitement around blockchain the technology is still poorly understood by many, so operators need to explore the practical applications of blockchain and investigate whether developing these capabilities would be beneficial and understand what will be their role telcos in this field. 

Machine learning, Artificial Intelligence (AI), Robots

Not many people in the Operators and in general in the Telco sector can explain what will be the practical potential of AI and machine learning in this sector. Other industry sectors are starting to apply machine learning models to their business. And as the technology and algorithms become more refined, early adopters expect to see huge cost savings. But at what cost? 

I expect to see real use cases for AI, machine learning and Robots to make the eternal promise of Customer Experience happen.

Will Telcos someday use machine learning and AI to learn about customer’s habits so that their services and product features can emulate a human behaviour more accurately?. This is a huge opportunity for both vendors and operators.

The wandering souls network

The first time I visited MWC as CEO of OIES, that is to say, as an independent consultant, I feel like a walking dead. Without a clear agenda, without scheduled meetings. I walk through hundreds of exhibitor booths looking for friend’s faces that can spend a couple of minutes to tell them my history.

The Telco sector (Operators, Large Vendors) and the IT sector is being very cruel with employees over 45 years old. This year I have had the opportunity to spend some time with some of ex-colleagues, friends and also LinkedIn contacts that wanted to tell me their history and asked me for advice about the new “El Dorado world of IoT”. 

There is a lot of talent out there. Do not exclude this extraordinary wandering network because you believe they are overqualified and you can not manage them.

See you next year at MWC18

I've been saying the same thing for years when I come exhausted from MWC  “No more tricks, no more illusions, this has been my last year". But will be this time the real one. Do I need a sabbatical MWC?.

“Whether you passed 1 day, 3 days or a whole week of your life in the MWC17 illusionism, ask yourself: Was it worth it? “

Now you see me or not @MWC18.

 Thanks for your Comments and Likes

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Just what is Big Data ??

Big data is the collection of data that is part of our daily lives. It is the hundreds of million e-mails, likes on Facebook, and tweets we post online. It is the hundreds of thousands of photographs that go live on the internet each day. The industry itself is one that is growing at a breakneck pace. In 2013 big data accounted for a $10.2 billion industry, but is estimated to reach an astonishing $54.3 million this year.

Big data does not necessarily focus on the amount of data that is used though. On the contrary, it can refer to what organizations do with this data. It is the analysis of this data, processing information to make more informed decisions, and reviewing trends to make better execute strategic business moves.

The concept behind big data isn’t a new one either. While you’ve likely just started to hear the term, the process of gathering information and storing it has been around for decades. It wasn’t until Doug Laney who is a renowned industry analyst touched on the volume of data, the velocity of data, and the variety of data that we had a vision closer to our modern trend. Expanding on his statement, we also note that there are other essential factors like complexity of data and variability that are a critical part of the analytical process.

In our modern world, the data that is around is always growing. There is currently no end in sight to where this big data will go and we will continue to discover and create new ways to store and analyze the data that is there. Perhaps most surprising is that despite the sheer amount of data that is out there, only a small percentage of it is regularly analyzed. That means that there is still a world of information out there that can be processed and the statistics from it can be used to further propel the understanding of data that is there.

What is important to note is that big data isn’t about the vast amount of data is there. It’s true the numbers are staggering, but there is much more to this. But when someone talks about big data, the focus is on what they can take and pull from the information. It is the analysis of the different aspects of it. This information will allow businesses to determine how information can be better processed so they can reduce their standard operating costs, reduce processing time, and discover new ways to optimize the data that they are collecting. Over a period of time, this will also allow individuals to make better decisions and to avoid failures and other problematic concerns that may be faced along the way.

Big data will remain a pivotal part of the future. It impacts the buying habits of our customers, determining the risk doing business with individuals and companies out there, and avoiding fraud before it happens. All while reviewing data that potentially helps us to further expand our reach and success for years to come. 

About Bill McCabe/ Internet of Things Recruiting - Executive Search/ Retained Search for the Internet of Things/ Machine 2 Machine/ Big Data Markets

IBM IOT Futurist - see you at #IBMInterconnect - March 19-23 Las Vegas

Top 50 IOT Authority on Twitter - per IoT Central

Need Help finding your next Big Data or IOT Employee or If you require the top 5% of IOT talent let’s talk. Drop me a line or use this link to schedule an IOT Search Assessment Call Click Here to Schedule

OR Contact me at 303-337-7871

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It was a matter of time to end up writing an article to talk about the connection between Internet of Things (IoT) and the technology (arguably still in the infancy of its development) that may have the greatest power to transform our world, Blockchain.

In a future planet interconnected not just by devices, but by the events taking place across it, with billions of devices talking to one another in real time, the Internet of Things will require a secure and efficient way to track all interactions, transactions, and activities of every “thing” in the network.

Blockchain’s role could be a coordination layer across devices and the enabler of the IoT to securely facilitate interactions and transactions between devices, and may also support certain processes related to architecture scalability, data sharing, and advancements in encryption and private key technology, enhanced security, and potentially even privacy.

With blockchain, the Achilles’ heel of the IoT of heterogeneous OEM devices world now becomes viable. I wonder however, if is feasible that this decentralized IoT network may co-exist IoT sub-networks or centralized cloud based IoT models.

But let's face it, blockchain is still a nascent and controversial technology (experts estimate that it might take 5 -10 years for the mainstream adoption of blockchain technologies). Therefore, we must consider that blockchain’s applications within the Internet of Things is still a matter of conjecture and trial, and that it will take more time to determine whether and how blockchain might be implemented to secure IoT ecosystems.

What is Blockchain?

Blockchain, the technology that constitutes the backbone of the famous bitcoin, is a database that maintains a continuously growing set of data records. It is distributed in nature, meaning that there is no master computer holding the entire chain. Rather, the participating nodes have a copy of the chain. It’s also ever-growing — data records are only added to the chain.

A blockchain consists of two types of elements:

  • Transactions are the actions created by the participants in the system.
  • Blocks record these transactions and make sure they are in the correct sequence and have not been tampered with. Blocks also record a time stamp when the transactions were added.

If you want to know more about blockchain you can read:

Fascinating opportunities ahead with IoT and Blockchain

The possibilities of IoT are virtually countless, especially when the power of IoT is combined with that of other technologies, such as machine learning. But some major hurdles will surface as billions of smart devices will want to interact among themselves and with their owners.

While these challenges cannot be met with the current models that are supporting IoT communications, tech firms and researchers are hoping to deal with them through blockchain.

Applying the blockchain concept to the world of IoT offers fascinating possibilities. Is yet to be seen if blockchain is bound to expedite the revolution, simply by being the backbone for most of the future IoT systems.

An example -  Right from the time a product completes final assembly, it can be registered by the manufacturer into a universal blockchain representing its beginning of life. Once sold, a dealer or end customer can register it to a regional blockchain (a community, city or state).  But, this is only the beginning for the blockchain and Internet of Things (IoT). A washing machine could become a semi-autonomous device capable of managing its own consumables supply. It can perform self-service and maintenance, and even negotiating with other peer devices.

Challenges of Blockchain and IoT ecosystems

The chaotic growth of IoT will introduce several challenges, including identifying, connecting, securing, and managing so many devices. It will be very challenging for the current infrastructure and architecture underlying the Internet and online services to support huge IoT ecosystems of the future.

Forrester analyst Martha Bennett in the report “Disentangle Hype From Reality: Blockchain’s Potential For IoT Solutions defines three categories of challenges that Internet of Things and blockchain ecosystems participants must address: Technology, Operational challenges and Legal and compliance issues.

According with the report, the result of multiple surveys indicates that what the IoT requires more than any technological or architectural advancement is trust: trust between stakeholders and the devices interacting with them, their customers, or on their behalf.

 “As technology and commercial firms look for ways to deploy and secure Internet of Things technologies at scale, blockchain has emerged as a clear favorite for managing issues like identity and transaction security”

Blockchain, a strategic ally to Democratize the IoT

The big advantage of blockchain is that it’s public, so there is no single authority that can approve the transactions or set specific rules to have transactions accepted. Thus, the primary utility the blockchain is a censorship resistant way to exchange value without intermediaries.

Will blockchain disrupt the disrupters?.  In my post “Is it possible to democratize the Internet of Things? How to avoid that a handful of companies can dominate the IoT” I already suggested the use of blockchain to avoid that data-hungry businesses and governments collect data on the behaviour of people and the performance of objects. Blockchain could avoid that Multinational and governments deepening tracking and control of citizen behaviour and attitudes. 

Are IoT Business Models at risks with Blockchain?

IoT Service Providers hope not. There is a risk that the combo of blockchain and the sharing economy trashes some new IoT business models.  Same way that, successful or not as successful platform, companies like Uber and Airbnb, are worried today.

Just think, the success of these and some other platform companies is largely due to people trading assets they own and are paid for, but from which new value could be derived, And they release this value by using platforms to match up sellers of the extra capacity – whatever it may be – with buyers. Further, they collect data about transactions “for further commercial gain”.

Indeed, arguably many of new IoT companies’ main line of business will be data, but, what if blockchain enabled buyers and sellers to work peer-to-peer and cut out the middleman/data aggregator and seller? In that case the secure connectivity could be king not the data.

A question for IoT Platform vendors, if we have a secure, foolproof decentralized system, why do I need your IoT Platform if I and all the communities I belong to can do it for ourselves, without anybody collecting, analyzing and selling data about me?

The convergence of Blockchain and the Internet of Things closer

In my post “Will we be able to build the Internet of Things?” I warned about the Babel tower of Alliance & Consortiums in the Internet of Things.

A blockchain technology industry consortium is emerging from the meeting, New Horizons: Blockchain x IoT Summit,  with the objective of defining the scope and implementation of a smart contracts protocol layer across several major blockchain systems.

In December 2016, representatives from a group of industry-leading startups and innovative Fortune 500 companies met in Berkeley, CA to discuss the challenges facing blockchain and IoT innovation and the potential for a collective effort to address them.  The meeting was the first step towards a collaborative effort to explore and build a shared blockchain-based Internet of Things protocol. Participants in the discussions included blockchain companies Ambisafe, BitSE, Chronicled, ConsenSys, Distributed, Filament, Hashed Health, Ledger, Skuchain, and Slock.it, along with Fortune 500 corporations BNY Mellon, Bosch, Cisco, Gemalto, and Foxconn.

Who is using Blockchain in IoT

The IoT and blockchain combination is already gaining momentum, and is being endorsed by both startups and tech giants. Several companies are already putting blockchain to use to power IoT networks.

Filament, a startup that provides IoT hardware and software for industrial applications such as agriculture, manufacturing, and oil and gas industries. Filament’s wireless sensors, called Taps, create low-power autonomous mesh networks that enable enterprise companies to manage physical mining operations or water flows over agricultural fields without relying on centralized cloud alternatives. Device identification and intercommunication is secured by a bitcoin blockchain that holds the unique identity of each participating node in the network.

Telstra, Australian telecommunication giant Telstra is another company leveraging blockchain technology to secure smart home IoT ecosystems. Cryptographic hashes of device firmware are stored on a private blockchain to minimize verification time and obtain real-time tamper resistance and tamper detection. Since most smart home devices are controlled through mobile apps, Telstra further expands the model and adds user biometric information to the blockchain hashes in order to tie in user identity and prevent compromised mobile devices from taking over the network. This way, the blockchain will be able to verify both the identity of IoT devices and the identity of the people interacting with those devices.

IBM, allows to extend (private) blockchain into cognitive Internet of Things. To illustrate the benefits of blockchain and Internet of Things convergence, IBM gives the example of complex trade lanes and logistics whereby smart contracts can follow (and via blockchain technology register), everything that has happened to individual items and packages. The benefits: audit trails, accountability, new forms of contracts and speed, to name a few.

IBM and Samsung introduced their proof-of-concept system, ADEPT, which uses blockchain to support next-generation IoT ecosystems that will generate hundreds of billions of transactions per day.

Onename are creating the infrastructure for blockchain based identities that can be used for humans and machines. This means the blockchain can act like a phone book that lets machines find each other.

Tierion is being used to collect data from industrial medical devices to build a verifiable record of their usage and maintenance history. Tierion is thrilled to be the first partner to join Philips' Blockchain Lab. Together they are exploring how blockchain technology can be used in healthcare.

ConsenSys working with Innogy (a subsidiary of German utility RWE) are exploring how to enable an energy marketplace fed by distributed solar and other electricity-generating devices, which are run using a decentralized power grid.

21.co, Microsoft, Slock.it, and others are working directly with adopters in manufacturing, supply chain management, energy and utilities, agriculture, and construction; distributed ledgers may further automate, secure, and drive new services for these industries.

Blockchain is not the unique silver bullet for IoT security

Given the importance that Security has to fulfil the promise of the Internet of Things (IoT), I wrote Do not stop asking for security in IoT although I did not talk about how blockchain can help secure the Internet of Things. Now with this post, I hope I have corrected that gap.

The existing security technologies will play a role in mitigating IoT risks but they are not enough. Cryptographic algorithms used by blockchain technologies could perhaps be a silver bullet needed by the IoT industry to create a more resilient ecosystem for devices to run on and to make consumer data more private. But blockchain should not be viewed as the unique silver bullet to all IoT security issues considering that today’s blockchain space is even more nascent than the IoT.

Manufacturers, legislators, IoT hardware and software vendors, IoT Service Providers, System Integrators, analyst, and end users, must be aware of the IoT security challenges and focus on increase security efforts to reduce the risk inherent to the fragmented Internet of Things so among all we can accelerate adoption.

In the long term, we should keep dreaming in a fully decentralized and secure IoT using a standardized secure communication model. We must trust this dream will be possible, if worldwide, engineering talent, startups, large companies, and governments increase the investment in time, energy, and money to innovate in solutions that address the IoT’s and blockchain’s shared problems.

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The Internet of Things is slated to be one of the most disruptive technologies we’ve ever seen. It’s going to change a great deal - including how we look at and use the cloud.

Software-defined cars. Internet-connected ‘smart’ fridges, coffee machines, and televisions. Wearable technology like smartwatches and smartglasses. The Internet of Things is going to change everything from how we work to how we drive to how we live our lives. And as it does so, it’s also going to change the cloud.

It already is, actually.

Enter fog computing. It’s an extension of the cloud, born out of the fact that there are more Internet-connected devices in the world than ever before (by 2020, Gartner predicts that there will be 6.4 billion.)  Given this influx, the traditional, centralized model of the cloud is no longer viable.

“Today, there might be hundreds of connected devices in an office or data center,” writes Ahmed Banafa of Thoughts On Cloud. “In just a few years, that number could explode to thousands or tens of thousands, all connected and communicating. Most of the buzz around fog has a direct correlation with IoT. The fact that everything from cars to thermostats are gaining web intelligence means that direct user-end computing and communication may soon be more important than ever.”

It makes a lot more sense to move the real computing and processing closer to client devices. To carry out analysis at the network’s edge. See, the thing about the Internet of Things is that it depends on managing data over very short timeframes. Even a slight delay introduced as a result of bandwidth is unacceptable.

Consider the following examples:

  • A self-driving car is communicating with the vehicles and traffic infrastructure around it, and analyzing traffic and weather conditions. While it may communicate with a central server, it needs to be able to analyze and aggregate data immediately, lest it cause an accident.

  • Autonomous tunneling and boring machines at a mining site ensure workers don’t have to subject themselves to hazardous underground conditions. These machines must be capable of analyzing and storing terabytes of data, as network connectivity hundreds of feet underground is near-impossible. They also must be able to communicate with other mining infrastructure, as well as a central server, uploading processed data to the cloud when mining is finished.

  • Sensors at an oil well must connect to a cloud server to provide headquarters with a real-time vision of the facility. These sensors, however, must be capable of analyzing data on-site before it is uploaded.

In each of the examples above, distributed computing works together with a more traditional cloud model to better-enable connected equipment and sensors. And that’s where the cloud slots in with IoT. It’s still the cloud - but it’s changed in order to adapt to new workflows, business processes, and an entirely new world.

“With the increase in data and cloud services utilization, fog computing will play a key role in helping reduce latency and improve the user experience” writes Data Center Knowledge’s Bill Kleyman. “We are now truly distributing the data plane and pushing advanced services to the edge. By doing so, administrators are able to bring rich content to the user faster, more efficiently, and - very importantly - more economically.”

Photo credit: Mr. & Mrs. Gray

About the Author:

Tim Mullahy is the General Manager at Liberty Center One. Liberty Center One is a new breed of data center located in Royal Oak, MI. Liberty can host any customer solution regardless of space, power, or networking/bandwidth requirements.

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