Subscribe to our Newsletter | To Post On IoT Central, Click here


Data (83)

Numerous Reasons Why Digital Transformation Fails

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!
Read more…

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

Read more…
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 withsmartphone, 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.
Read more…

MWC- The Great Illusionists Show

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

Read more…

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.

Read more…

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.

Read more…

A Fresh Approach to Remote IoT Connectivity

The IoT market has changed in many ways throughout the years, and since it’s a growing industry, there’s an estimated 32.6% CAGR increase in the next five years.

 

As an industry predicted to spend trillions in solutions, IoT’s trends need to be carefully observed and examined in order for implications and applications to be future-proofed.

 

How do you go about doing this? By simply analyzing how IoT is being used, as well as identifying which sectors are showing potential growth. Right now, a lot of focus is given to consumer applications such as Amazon’s dash buttons and smart home appliances. However, there are many opportunities in remote IoT. This covers industries like industrial, transportation, healthcare, etc.

 

One challenge that needs to be dealt with is how connectivity is approached right now. As more IoT and M2M devices would be deployed in rural areas and places with limited connectivity, applications and machines would need an improved infrastructure in order to carry out their purpose in areas with little connectivity.

 

Additionally, the increase of transportation and emergency-related applications would require not only ways to deals with low connectivity but also call for a system that can access multiple networks depending on availability and location.

 

Another challenge is how current devices will handle the developments in IoT and M2M technologies in the next five years. The 2G sunset is just one-way communication companies are affecting the industry.

 

Don’t fret, though, as there are several ways to resolve this and many opportunities left to explore to get ready for IoT’s evolution in the coming years.

 

Want to learn more about the possibilities remote IoT connectivity presents and how you can prepare for them? Check out the following infographic from Communications Solutions Company, Podsystem, and start future-proofing your IoT and M2M applications.

Read more…
Internet of Things (IoT) began as an emerging trend and has now become one of the key element ofDigital Transformationthat is driving the world in many respects.
If your thermostat or refrigerator is connected to the Internet, then it is part of the consumer IoT.  If your factory equipment have sensors connected to internet, then it is part of Industrial IoT(IIoT).
IoT has an impact on end consumers, while IIoT has an impact on industries like Manufacturing, Aviation, Utility, Agriculture, Oil & Gas, Transportation, Energy and Healthcare.
IoT refers to the use of "smart" objects, which are everyday things from cars and home appliances to athletic shoes and light switches that can connect to the Internet, transmitting and receiving data and connecting the physical world to the digital world.
IoT is mostly about human interaction with objects. Devices can alert users when certain events or situations occur or monitor activities:
·       Google Nest sends an alert when temperature in the house dropped below 68 degrees
·       Garage door sensors alert when open
·       Turn up the heat and turn on the driveway lights a half hour before you arrive at your home
·       Meeting room that turns off lights when no one is using it
·       A/C switch off when windows are open
IIoT on the other hand, focus more workers safety, productivity & monitors activities and conditions with remote control functions ability:
·       Drones to monitor oil pipelines
·       Sensors to monitor Chemical factories, drilling equipment, excavators, earth movers
·       Tractors and sprayers in agriculture
·       Smart cities might be a mix of commercial and IIoT.
IoT is important but not critical while IIoT failure often results in life-threatening or other emergency situations.
IIoT provides an unprecedented level of visibility throughout the supply chain. Individual items, cases, pallets, containers and vehicles can be equipped with auto identification tags and tied to GPS-enabled connections to continuously update location and movement.
IoT generates medium or high volume of data while IIoT generates very huge amounts of data (A single turbine compressor blade can generate more than 500GB of data per day) so includes Big Data,Cloud computingmachine learning as necessary computing requirements.
In future, IoT will continue to enhance our lives as consumers while IIoT will enable efficient management of entire supply chain.
Read more…
How many times you have listened to the advice of your friend/colleague or someone you know, to invest in stock market? Many people have gained and lost their fortune with this guess work and now younger generation is more scared to hand over their hard earned money to someone for investing.
Until recently, you had 2 options for investments - either hire a human financial advisor or do it yourself. Human advisors charge substantial fees starting minimum 1% of value of assets to manage your portfolios. Do it yourself option requires lot of time and energy and you may lose your money due to result of overtrading, panic-selling during downturns, and trying to time the market as the issue for many individuals is they aren’t cut out to go it alone
This is where robo-advisors have scored more over humans.
A robo-advisor is an online, automated wealth management service based on data science algorithms with no or minimal human interventions that allocate, deploy and rebalance(spreading your money in stocks, mutual funds, bonds to balance risks) your investments.
The robo-advisor industry is in its infancy. Online life is migrating from persona desktop computing to laptops to tablets and finally to mobile.
Here are some of the advantages of using a robo-advisor:
·       Cheaper fees or free compared to traditional financial advisors
·       Automatic diversification into various options
·       Easy online access as we all are accustomed to shiny apps on mobile
·       Safer than picking your own stocks
·       You don’t need a degree in finance to understand the recommendations.
Big data and advanced analytics can help broaden the scope of robo-advice dramatically, incorporating financial planning into broader retirement planning, tax planning, vacation savings, higher education planning.
Robo-Advisors have typically targeted millennials segment because these young investors want to save & multiple money faster and often don't have enough patience & wealth to warrant the attention and interest of a human advisor.
High Net worth Individuals also think, online and automated investment tools can positively affect their wealth manager's advice and decision-making.
Overall, robo-advisors provide a good user experience with latest digital technologies such as slick apps and fancy interfaces. These platforms make sure that they fit right in with your daily online browsing,  and are great options for novice investors who are just starting out and want to dip their toes in the world of investments, or for people with a simple financial plan who just need an affordable, straightforward place to start their retirement plans
Wealthfront & Betterment are two popular commercial fee based robo-advisors available today. In the Free category WiseBanyan & CharlesSchwab are making the ground.
But it won’t be long before Amazon, Google, Facebook and Apple get in on the robo-advisor industry.
Robo advice is certainly here to stay, and it has its place in the wealth management landscape of tomorrow. But what's missing most, with robo-advisers is the personal touch.  In this age of hyper-personalization, the lack of a human element is one area where robo-advisors may fall short.
The robo-advisor can't replace a trusted age old adviser, your elders have worked with, who lives nearby and can rush right over in case of need, who knows you and your family.

With the pace of improvement that Artificial Intelligence and machine learning bringing up, robo-advice has the potential to become highly personalized and specific over time.
Read more…
In very simple terms, Business model is how you plan to make money from your business. 
A refined version is how you create and deliver value to customers. Your strategy tells you where you want to go and the business model tells you how you are going to do it.
In this time of industry 4.0 with Digital Transformation, businesses are getting disrupted faster than they get established. We all know what Apple did for music, Uber did for taxis and Airbnb did for hotels.
Digital is helping them to enhance their existing products and services and helping to launch new products and services.
Companies are using various business models to be successful:
  • Freemium model : Basic products/services are provided free but       users are charged for advance features. E.g. Coursera, LinkedIn, Spotify, Dropbox, Skype
  • Pay as you go or Subscription Model : Pay only for services which are used. E.g. Netflix, Kindle, New York Times, Safari Books online
  • Customer experience model : provide the customer experience never before e.g. Tesla, Disney Land, Apple
  • On-Demand model : provide customer service on demand with speed. E.g. Uber, cloud services from Amazon, Microsoft
  • Marketplace model : provide a platform for buyer and seller interact with each other directly e.g. ebay, Alibaba
  • Free model : provide the typical services to users free and sell their behavior data to different businesses e.g. Google, Facebook, Patientslikeme
  • Crowd-sourcing model : receive money for engaging crowd for common goal, innovation, problem solving. E.g. Kaggle, CrowdAnalytix
  • Bundling model : selling similar products or services together. E.g. Microsoft Office        
  • Gamification model : use of game like feature to simplify the interaction. E.g Mint.com, Khan Academy, Nike +
 
Some of the big companies moved on from their core business model and adopted to the change embracing digital to get closer to customers in real time and grow exponentially.
Nike had moved on from a sports apparel company to fitness driven personalized wearables like FuelBand manufacturer.
Amazon started in 1995 as on online book store but went on to become leader in technologies like CloudDrones, web services. 
Philips started as Light Bulb Company and moved on to become leader in healthcare equipment’s touching millions of people lives.
GE has moved forward from its core industrial products – from jet engines and gas turbines to CT/PET scanners, locomotives with sensors that monitor various parts of the machinery. They developed their own Predix IoT platform with advanced analytics to provide real time information to improve efficiency, increase productivity, and schedule more effective preventive maintenance.
Apple adopted multiple models from PC manufacturer to selling online music, to subscription model of iCloud.
Changing the business model drastically may not work. Don’t try to boil the ocean but start with how you can deliver greater value to customers through digital technology.
Success in choosing one business model over another, will depend on how well companies understand their customers’ needs. 
Read more…
Do you still remember our childhood story of Ali Baba and 40 thieves?
“Open Sesame” was the magical phrase that a poor woodcutter Ali Baba uttered, to open the door of a secret cave in which 40 thieves had hidden bags of gold and treasure. The power of his voice, and using the right words, gave him access to that fortune, and changed his life forever.
We are in the same cusp of open sesame to Digital Transformation and changing our lives. It’s a fact that our lives are becoming more digital. We buy, we work, we store information, and we even communicate with other people through media and digital platforms.
A laptop was not an item in my life until the age of 35, whereas for my daughters, they have always had a laptop in the house, and learned how to use it, earlier than me.
Whether we like it or not, digital transformation is creating a new era… changing how we do things, how we live … and we are already fully immersed into it. We have a great opportunity to be more effective, efficient, fast and agile.
We, as consumers expect ultra-connected experiences. Whether it’s in-store, on the web, using a mobile device or through wearables, we want every interaction to be simple, effortless, relevant and lightning fast.
The Internet of Things have already started changing our lives!! The connected car we use may know the temperature we like at home so adjust accordingly. The mobile app is connected with all Smart Home devices to alert us of anything suspicious happening while we are away. It can notify when we approach grocery store, of the items we need at home. With Drones, we can get a tour of properties listed so we can choose the right one.
To reach 50 million users, radio took 38 years, Google took 6 years, and Google+ needed just 88 days while Smartphone “Pokémon Go” game reached that count in just 19 days!!
Our lives have become a collection of mobile moments in which we pull out a mobile device as if it was a magic wand to get something done wherever and whenever we want. We use smartphones for more than just making phone calls. From online banking to posting family photos to social media, sending e-mails and text messages, searching for restaurants and booking movies.
We are alerted of our days’ appointments and meetings before even we had our breakfast. A weather app alerts us of the rain forecast. To make our commute pleasant, the built-in GPS in our car alerts us of upcoming traffic along the planned route and suggests an alternative route so we can get to work on time and keep our meetings.
All of us have become so health conscious with wearables like Apple watch & activity trackers like Fit bit and Jawbone and Google smart contact lenses etc. With wearables like Oculus Rift VR, we can enter into an exciting new realm of augmented reality, with an enhanced experience of what we see, hear and touch.
Big Data Analytics is an ideal entry point to get into digital transformation.  It is like turning the lights on in a dark room. Every interaction we have with businesses, point-of-sale transaction details, loyalty card information, surveys, and social media postings to Facebook, Twitter, Pinterest, and more.. which provides deep insight into our behavior, attitudes, and opinions that businesses are leveraging to improve relationships with hyper-personalization.
Voila! Life is simplified …..

Was this all available to us 20 years before? Ali Baba’s “Open Sesame” was a story of childhood, but Digital Transformation is reality – and from now on nothing will be same again.

Read more…

What will this market bring us in the next few years? Are there reasons for optimism?

During the last three years, I have had the opportunity to discover, know and analyse more than 50 Spanish companies in the exciting sector of the Internet of Things (IoT).

Some of these companies are globally recognized as pioneers of IoT. Others less known but very innovative, with great talent in their ranks. All of them have been weathering the storm and far from being discouraged, because the reality is being tougher than all the hype announced by analysts, are more excited than ever before future expectations.

As I wrote in my post “5 PROVERBS TO SAVE MY STARTUP”, nobody is a prophet in their land, but even so, I can not resist providing a few tips that I believe can help us use IoT as an enabler that drives the ICT sector. Would not it be fantastic if we finally met our desire to have a strong, dynamic, competitive and innovative ICT sector in our society?

Accept reality

And the stark reality is: "Spain is not a technological country, it is a service country". I think that the lapidary expression of Miguel de Unamuno, that “they invent it”, also applies to the IoT. But it is one thing not to invent and another is to become sellers of products, solutions or services of multinationals by all known.

We must use our ingenuity, talent, creativity, and customer orientation to design and develop quality, easy-to-use global IoT solutions.

If we are good sellers of foreign products, the language should be the problem. Our objective market should not be our City, our Community or our Country, our market must be the world.

Focus, Focus and Focus

I have insisted on many forums that in Spain we can not do everything on IoT. For example, we can be leaders in Smart Cities, but we will have little chance of success in Connected Cars, we must fight to find a gap in Industry 4.0 (also known as Industrial Internet or IIOT) but I fear we will not be number 1 in Wearables, although we could be innovative in Health services.

We must analyse our strengths and weaknesses to recognize where our opportunities are and what our threats are. Let us be references in our focus areas.

Trusted Ecosystems

We know that there is not a single company in the world that can do everything in IoT, much less leading the IoT, so it is obvious that our companies and Startups have no other choice than to create or be part of reliable ecosystems and Collaborative projects in the focus areas to meet the challenges posed by IoT projects.

We must design new sustainable business models with our local partners, it is time to trust if we want to survive in this competitive and fragmented sector until the magic 2020.

It's time to real collaboration, put a logo on our presentations and our website is absurd if there is something else behind.

Specialization

Given the size of IoT Spanish companies it is not possible to do everything and get it right.

We must specialize, whether manufacturing specific hardware, developing software or offering services in our focus areas.

Scalability

To succeed in IoT, Spanish companies must be able to offer global and scalable solutions. We will need startup talent to focus on companies of a larger size than without giving up innovation and agility, being able to cope with large national and international IoT projects.

Expect to be outsourced by other subcontractors of a company that works for an end customer is not acceptable if we really want to change. It is a pending subject of our business model not only in technology, it is a deep-seated problem of corporate culture.

We should be able to have at least one unicorn in IoT. And I'm not talking about Telefonica, Banco Santander, BBVA, Iberdrola, Inditex, ACS, Ferrovial or Indra, but a company that provides a new IoTaaS model based on our strengths (which all or almost all know) Services and HW / SW IoT products from Spanish manufacturers. That is, we must think about having our Uber, Airbnb or why not our Spanish Tesla.

We must look for concentration of companies in the focus areas to achieve the size that allows the scalability that the IoT business needs.

Invest in Education and Training

The IoT is complex, although many try to make it simple. We will need many types of profiles and not just theoretical knowledge.

It is vital at both, the private and public levels, that the Public Administrations and Companies dedicate funds to continuously educate students and train employees in the IoT technologies.

 “Investing now in IoT training will be key to ensuring a sustainable future for our companies, our country and our professionals.”

 Start Now

This advice goes to both Enterprises and Public Administrations.

In the case of Enterprises, it would be highly desirable to lose for once the fear of being the first to implement technology solutions. You must consider IoT a key element in the digitization process of your company.

Public Administrations, stop using your budgets as always, and think about investing in a more sustainable, intelligent and connected citizen.

To conclude, pulling on the proverb I think:

"We have the wicker, so we must have confidence that we can make a great basket in IoT".

You can read the Spanish version here.

Thanks in advance for your Likes and Shares

Thoughts ? Comments ?

Read more…
Today, with Digitization of everything, 80 percent the data being created is unstructured. 
Audio, Video, our social footprints, the data generated from conversations between customer service reps, tons of legal document’s texts processed in financial sectors are examples of unstructured data stored in Big Data.
Organizations are turning to natural language processing (NLP) technology to derive understanding from the myriad of these unstructured data available online and in call-logs.
Natural language processing (NLP) is the ability of computers to understand human speech as it is spoken. NLP is a branch of artificial intelligence that has many important implications on the ways that computers and humans interact. Machine Learning has helped computers parse the ambiguity of human language.
Apache OpenNLP, Natural Language Toolkit(NLTK), Stanford NLP are various open source NLP libraries used in real world application below.
Here are multiple ways NLP is used today:
The most basic and well known application of NLP is Microsoft Word spell checking.
Text analysis, also known as sentiment analytics is a key use of NLP. Businesses are most concerned with comprehending how their customers feel emotionally adn use that data for betterment of their service.
Email filters are another important application of NLP. By analyzing the emails that flow through the servers, email providers can calculate the likelihood that an email is spam based its content by using Bayesian or Naive based spam filtering.
Call centers representatives engage with customers to hear list of specific complaints and problems. Mining this data for sentiment can lead to incredibly actionable intelligence that can be applied to product placement, messaging, design, or a range of other use cases.
Google and Bing and other search systems use NLP to extract terms from text to populate their indexes and to parse search queries.
Google Translate applies machine translation technologies in not only translating words, but in understanding the meaning of sentences to provide a true translation.
Many important decisions in financial markets use NLP by taking plain text announcements, and extracting the relevant info in a format that can be factored into algorithmic trading decisions. E.g. news of a merger between companies can have a big impact on trading decisions, and the speed at which the particulars of the merger, players, prices, who acquires who, can be incorporated into a trading algorithm can have profit implications in the millions of dollars.
Since the invention of the typewriter, the keyboard has been the king of human-computer interface. But today with voice recognition via virtual assistants, like Amazon’s Alexa, Google’s Now, Apple’s Siri and Microsoft’s Cortana respond to vocal prompts and do everything from finding a coffee shop to getting directions to our office and also tasks like turning on the lights in home, switching the heat on etc. depending on how digitized and wired-up our life is.
Question Answering - IBM Watson is the most prominent example of question answering via information retrieval that helps guide in various areas like healthcare, weather, insurance etc.
Therefore it is clear that Natural Language Processing takes a very important role in new machine human interfaces. It’s an essential tool for leading-edge analytics & is the near future.
Read more…

Guest blog post by Olga Kolesnichenko

What is Big Data: data, process of analysis or concept? There are many definitions that describe Big Data as big amount of data or as some methods of analytics of big amount of data. But more applicable is the approach that Big Data is the concept that includes: data with specific characteristics (V3 - volume, velocity, variety, or V5 - plus value and veracity), methods of analytics (the number of different software is growing), and devices, infrastructure, and most important - the ideas how to configurate all into needed solution.

Another concept is the Internet of Things that based on Big Data Analytics. There are some established configurations of IoT: Smart Home, Smart Health, Smart Manufacturing, Smart City, Smart Mobility, Smart Energy, Smart Farming, Smart Earth & Ocean, Smart Circular Economy.

Smart Health or Internet of Health (or any IoT configuration) has the human in core of concept. I should point out that more easy to accept the medical approaches for different configurations of IoT than accept IoT approaches for Health Care. Why I can insist on this statement? My statement leans on long-term period of complexity of accepting biorhythmology and gravitational biology in medicine.

But biorhythmology and gravitational biology have the direct application for Internet of Health or IoT. The person controls own different medical data day by day during everyday life. And this new situation should be viewed as medical data collecting under gravitational forces and natural biorhythms influences to person.

Three sections of multifactorial regulation of human body should be mentioned: environmental, behavioral and homeostatic. Environmental section includes circannual rhythm (annual) and circadian rhythm (daily). Behavioral section includes body orientation towards gravitational forces (lying down, standing, sitting); active movement (walking, jogging, exercises); passive movement (lift and transport) with influence of acceleration forces; as well as sleep, emotional reactions, eating. Homeostatic section includes the processes of neurohumoral regulation of the body. This section consists of functional systems of the body, described by Russian scientist K.V. Sudakov and his following.

Thus creating Internet of Health configuration and implementing Big Data Analytics the medical data should be considered in terms of three sections of multifactorial regulation of human body. 

Read more…

This is how Analytics is changing the game of Sports!!

Analytics and Big Data have disrupted many industries, and now they are on the edge of scoring major points in sports. Over the past few years, the world of sports has experienced an explosion in the use of analytics
Till few years back experience, gut feelings, and superstition have traditionally shaped the decision making process in sports.
It is first started with Oakland Athletics' General Manager, Billy Beane, who applied analytics for selecting right players. This was the first known use of statistics and data to make decisions in professional sports.
Today, every major professional sports team either has an analytics department or an analytics expert on staff.  From coaches and players to front offices and businesses, analytics can make a difference in scoring touchdowns, signing contracts or preventing injuries.
Big name organizations such as the Chicago Cubs, and Golden State Warriors are realizing that this is the future of sports and it is in their best interest to ride the wave while everyone else is trying to learn how to surf.
Golden State Warriors, have similarly used big data sets to help owners and coaches recruit players and execute game plans.
SportVu has six cameras installed in the NBA arenas to track the movements of every player on the court and the basketball 25 times per second. The data collected provides a plethora of innovative statistics based on speed, distance, player separation and ball possession to improve next games.
Adidas miCoach app works by having players attach a wearable device to their jerseys. Data from the device shows the coach who the top performers are and who needs rest. It also provides real-time stats on each player, such as speed, heart rate and acceleration.
Patriots developed a mobile app called Patriots Game Day Live, available to anyone attending a game at Gillette Stadium. With this app, they are trying to predict the wants and needs of fans, special content to be delivered, in-seat concession ordering and bathroom wait times.
FiveThirtyEight.com, provides details into more than just baseball coverage. It has over 20 journalists crunching numbers for fans to gain a better understanding of an upcoming game, series or season.
Motus’ new sleeves for tracking a pitcher’s throwing motion, measuring arm stress, speed and shoulder rotation. The advanced data generated from this increases a player’s health, performance and career. Experts can now predict with greater confidence if and when a pitcher with a certain throwing style will get injured.

In the recent Cricket world cup, every team had its own team of Data Analysts. They used various technologies like Cloud Platform and visualizations to predict scores, player performance, player profiles and more. Around 40 years’ worth of Cricket World Cup data is being mined to produce insights that enhances the viewer's experience. 
Analytics can advance the sports fans' experience as teams and ticket vendors compete with the at-home experience -- the better they know their fans, the better they can cater to them.
This collection of data is also used for internet ads, which can help with the expansion and growth of your organization through social media platforms or websites. 
  • What would be the most profitable food served at the concession stand?
  • What would be the best prices to sell game day tickets?
  • Determine which player on the team is the most productive?
  • Which players in the draft will become all-stars, and which ones will be considered role players?
  • Understand the fans behavior at the stadium via their app and push relevant information accordingly.
In this Digital age, Analytics are the present and future of professional sports. Any team that does not apply them to the fullest is at a competitive disadvantage.
Read more…

The Untapped Potential of Data Analytics

The potential of big data just keeps growing. For taking full advantage, companies need to incorporate analytics into their strategic objectives.

A research report from McKinsey Global Institute (MGI), suggests that the opportunity and applications continue to expand in the data-driven world.

With rapid technological transformation, the question for businesses arises on how to position themselves uniquely in the world leveraging analytics. Over 2.5 quintillion bytes of data is generated every day. As information pours in via various digital platforms, VR application, and mobile phones the need for data storage capacity has increased.

The transformational potential

The recent progress shows the potential of big data and analytics in more than five distinct domains. However, transforming to a data-driven decision-making organisation is not always simple.

The first challenge is to incorporate data and analytics along with business objectives into a core strategic vision. Secondly, the lack of talent in the adoption of analytics. New reports denote that despite training programs, the talent is not enough to match the demand. The next step is to develop the right business process and framework which includes data infrastructure.

Simply combining technology systems along with the existing business operations isn't enough. For ensuring a successful transformation, all aspects of business activity need to be evaluated and combined to realize the full potential of data analytics.

Incorporating data analytics

The next generation of analytic tools will unleash even bigger opportunities. With new machine-learning, deep-learning and artificial-intelligence capabilities, an enormous variety of applications can be enabled which provide customer service, manage logistics and analyze data.

Technology and productivity gains seem an advantage, but also carry the risk of people losing jobs. A case of automation is the AI software developed by Bridgewater Associates, the world's largest hedge fund to improve efficiency.

With Data and analytics shaking up every industry, the effects will only become more noticeable as adoption reaches the masses.

As machines gain unprecedented capabilities to solve complex problems, organizations can harness these capabilities to create their unique value proposition and solve problems.

 

Read more…

What are Microservices in Digital Transformation?

Today’s organizations are feeling the fear of becoming dinosaur every day. Newdisrupters are coming into your industry and turning everything upside down.
Customers are more demanding than ever and will abandon the service that is too slow to respond.  Everything is needed yesterday to make your customers happy.
Now, there is no time for organizations to implement huge enterprise applications which takes months and years. 
What they need is, more agile, smaller, hyper focused teams working together to innovate and provide customer value.
This is where Microservices have gain momentum and are becoming fast go-to solution for enterprises. They takes SOA a step further by breaking every component into effectively single-purpose applications.
Microservices, show a strategy for decomposing a large project, based on the functions, into smaller, more manageable pieces. While a monolithic app is One Big Program with many responsibilities, Microservice based apps are composed of several small programs, each with a single responsibility
Microservices are independently developed & deployable, small, modular services. Each component is developed separately, and the application is then simply the sum of its constituent components. Each service runs as a unique process and communicates with other components via a very lightweight methods like HTTP/Rest with Jason.
Unlike old single huge enterprise application which requires heavy maintenance, Microservices are easy to manage.
Here are few characteristics and advantages of Microservices:
  • Very small, targeted in scope and functionality
  • Gives developers the freedom to independently develop and deploy services
  • Loosely coupled & can communicate with other services on industry wide standards like HTTP and JSON
  • API based connectivity
  • Every service can be coded in different programming language
  • Easily deployable and disposable makes releases possible even multiple times a day
  • New Digital technology can be easily adopted for a service
  • Allows to change services as required by business, without a massive cost
  • Testing and releases easier for individual components
  • Better fault tolerance and scale up
There are some challenges as well, while using Microservices:
  • Incur a cost of the testing at system integration level
  • Need to configure monitoring and alerting and similar services for each microservice
  • Service calls to one another, so tracing the path and debugging can be difficult
  • Each service communicates through API/remote calls, which have more overhead
  • Each service generates a log, so there is no central log monitoring.
Netflix has great Microservice architecture that receives more than one billion calls every day, from more than 800 different types of devices, to its streaming-video API.
Nike, the athlete clothing and shoe giant & now digital brand is using Microservices in its apps to deliver extra ordinary customer experience.
Amazon, eBay are other great examples of Microservices architecture.
GE’s Predix - the industrial Internet platform is based on Microservices architecture.
So, if your IT organization is implementing a microservices architecture, here are some examples of an operating system (Linux, Ubuntu, CoreOS), container technology(Docker), a scheduler(Swarm, Kubernetes), and a monitoring tool(Prometheus).
The technical demands of digital transformation, all front/back-office systems that seamlessly coordinate customer experiences in a digital world is achieved by Microservices as the preferred architecture.
Microservices help close the gap between business and IT & are fundamental shift in how IT approaches software development and are absolutely essential in Digital Transformation.
Read more…

IoT Future – 34 Billion new Devices in 4 Years?

Many industry experts and consumers are pointing the Internet of Things (IoT) as an upcoming Industrial Revolution or an upcoming Internet.

Why this? Simple, because IoT will consist of the future form of interaction of businesses, governments and consumers with the physical world.

The most recent studies indicate that in 2020 more than 34 billion devices will be connected to the internet, in many sectors (Industrial, Agriculture, Transportation, Wearable Devices, Smart Cities, Smart Houses, etc).

Of these 34 billion, the IoT will be responsible for 23 billion devices, the others 11 billion will be represented by the regular devices, such as, smartphones, tablets, smartwatches, etc.

BI - IoT - Evolution Graph - IoT FutureSource: BI Intelligence

The business sector will be responsible for the biggest use part of this devices, since the IoT can reduce the Operational Costs, Increase the Production, expand the business for new market niches.

Government will take the second biggest part of the devices connected, in smart cities, fasting up the public process, increasing the quality life of the citizens.

At last but not less important, the home user, will have a lot of IoT Devices, Smart Houses, Wearable Devices.

So the future we can really specify in some words: "The future is Data".

Read more…

Do you know what is powerful real-time analytics?

In the Digital age today, world has become smaller and faster. 
Global audio & video calls which were available only in corporate offices, are now available to common man on the smartphone.
Consumers have more information of the products and comparison than the manufactures at any time, any place, and any device.
Gone are the days, when organizations used to load data in their data warehouse overnight and take decision based on BI, next day. Today organizations need actionable insights faster than ever before to stay competitive, reduce risks, meet customer expectations, and capitalize on time-sensitive opportunities – Real-time, near real-time.
Real-time is often defined in microseconds, milliseconds, or seconds, while near real-time in seconds, minutes.
With real-time analytics, the main goal is to solve problems quickly as they happen, or even better, before they happen. Real-time recommendations create a hyper-personal shopping experience for each and every customer.
The Internet of Things (IoT) is revolutionizing real-time analytics. Now, with sensor devices and the data streams they generate, companies have more insight into their assets than ever before.
Several industries are using this streaming data & putting real-time analytics. 
·        Churn prediction in Telecom
·        Intelligent traffic management in smart cities
·        Real-time surveillance analytics to reduce crime
·        Impact of weather and other external factors on stock markets to take trading decisions
·        Real-time staff optimization in Hospitals based on patients 
·        Energy generation and distribution based on smart grids
·        Credit scoring and fraud detection in financial & medical sector
Here are some real world examples of real-time analytics:
·        City of Chicago collects data from 911 calls, bus & train locations, 311 complaint calls & tweets to create a real-time geospatial map to cut crimes and respond to emergencies
·        The New York Times pays attention to their reader behavior using real-time analytics so they know what’s being read at any time. This helps them decide which position a story is placed and for how long it’s placed there
·        Telefonica the largest telecommunications company in Spain can now make split-second recommendations to television viewers and can create audience segments for new campaigns in real-time
·        Invoca, the call intelligence company, is embedding IBM Watson cognitive computing technology into its Voice Marketing Cloud to help marketers analyze and act on voice data in real-time.
·        Verizon now enables artificial intelligence and machine learning, predicting the customer intent by mining unstructured data and correlations
·        Ferrari, Honda & Red Bull use data generated by over 100 sensors in their Formula 
One cars and apply real-time analytics, giving drivers and their crews the information they need to make better decisions about pit stops, tire pressures, speed adjustments and fuel efficiency.
Real-Time analytics helps getting the right products in front of the people looking for them, or offering the right promotions to the people most likely to buy. For gaming companies, it helps in understanding which types of individuals are playing which game, and crafting an individualized approach to reach them.
As the pace of data generation and the value of analytics accelerate, real-time analytics is the top most choice to ride on this tsunami of information.
More and more tools such as Cloudera Impala, AWS, Spark, Storm, offer the possibility of real-time processing of Big Data and provide analytics,

Now is the time to move beyond just collecting, storing & managing the data to take rapid actions on the continuous streaming data – Real-Time!! 

Read more…

Originally posted by Vincent Granville

It's time again to share your predictions for 2017. I did my homework and came with these 10 predictions. I invite you to post your predictions in the comment section, or write a blog about it. Ramon Chen's predictions are posted here, while you can read Tableau's prediction here. Top programming languages for 2017 can be found here. Gil Press' top 10 hot data science technologies is also worth reading. For those interested, here were the predictions for 2016. Finally, MariaDB discusses the future of analytics and data warehousing in their Dec 20 webinar.

My Predictions

  1. Data science and machine learning will become more mainstream, especially in the following industries: energy, finance (banking, insurance), agriculture (precision farming), transportation, urban planning, healthcare (customized treatments), even government.
  2. Some, with no familiarity with data science, will want to create a legal framework about how data can be analyzed, how the algorithms should behave, and to force public disclosure of algorithm secrets. I believe that they will fail, though Obamacare is an example where predictive algorithms were required to ignore metrics such as gender or age, to compute premiums, resulting in more expensive premiums for everyone.
  3. The rise of sensor data - that is, IoT - will create data inflation. Data quality, data relevancy, and security will continue to be of critical importance.
  4. With the rise of IoT, more processes will be automated (piloting, medical diagnosis and treatment) using machine-to-machine or device-to-device communications powered by algorithms relying on artificial intelligence (AI), deep learning, and automated data science. I am currently writing an article that describes the differences between machine learning, IoT, AI, deep learning and data science. You can sign-up on DSC to make sure that you won't miss it. 
  5. The frontier between AI, IoT, data science, machine learning, deep learning and operations research will become more fuzzy. Statistical engineering will be present in more and more applications, be it machine learning, AI or data science. 
  6. Many systems will continue to not work properly. The solution will have to be found not in algorithms, but in people. Read my article Why so many Machine Learning Implementations Fail. An example is Google analytics, which fails to catch huge amounts of robotic traffic that is so rudimentary and so obvious, you don't need any statistical or data science knowledge to filter it or block it. People publish elementary solutions to address these issues, yet it continues unabated. Fake reviews, fake news, undetected hate speech on Twitter, undetected plagiarism by Google search, are in the same category. Eventually it leaves room for new players to jump in and build a system that will actually work. 
  7. Reliance on public data and public news will come with bigger scrutiny. Some say that the failure to predict the elections is a data science failure. In my opinion, it is a different type of failure: it is the failure to recognize that the media are biased (they publish whatever predictions that fit with their agenda) and maybe even those doing the surveys are biased or incompetent (there are lies, damn lies, and statistics as the saying goes). It is also a failure to recognize the very high volatility in these elections, and the fact that day-to-day variations were huge. Anyone able to compute sound confidence intervals that incorporates historical data,  would have said that the results were not reliably predictable. Finally, I always thought that the winner would be the one best able at manipulation and playing tricks, be it hacking or paying the media.
  8. More and more data cleaning, pre-processing, and exploratory data analysis will be automated. We will also face more unstructured data, with powerful ways to structure them.  Multiple algorithms and models will be more and more blended together to provide the best pattern recognition and predictive systems, and boost accuracy. 
  9. Data science education will evolve, with perhaps a come back of strong university curricula run by leading practitioners, and fewer people finding a job through data science camps only, as many of these camps do not train you to become a data scientist, but instead a Python / R / SQL coder with classic, elementary, even outdated and dangerous statistical knowledge. Or data camps will have to evolve, or otherwise risk becoming another kind of Phoenix university.
  10. Attacks against data-dependent infrastructure will switch from stealing or erasing data, to modifying data. Some will be launched from IoT devices if security holes are not fixed.

Follow us @IoTCtrl | Join our Community

Read more…
RSS
Email me when there are new items in this category –

Upcoming IoT Events

6 things to avoid in transactional emails

transactional man typing

  You might think that once a sale has been made, or an email subscription confirmed, that your job is done. You’ve made the virtual handshake, you can have a well-earned coffee and sit down now right? Wrong! (You knew we were…

Continue

More IoT News

IoT Career Opportunities