Mobile and Remote Workforces will be Necessary to Access Global Talent.The overall tech industry is already seeing talent gaps, especially when it comes to data scientists and data engineers. These advanced professionals go above and beyond programming, coding, and running analytics software but maintain strategic experience and expertise to evaluate overall business processes and operations, and know how to use the right tools, collate the most relevant data, elevate data for applications and response, and understand the ability to integrate with common business software and systems. Because we are already in a severe overall talent pool decline, companies will need to embrace the remote and global workforce like never before. This means the tools this new workforce uses will require enterprise chat, collaboration, any and mobile device access to business essentials, video conferencing, remote document management, and much more. READ MORE

​Compass Intelligence 2018 Tech Trends: A Review of Major Tech Trends and Highlights of the Annual Awards
Get the full Report HERE!

Most of the smartphone reviews out on the web today are based on the consumer perspective, that is why I wanted to provide a B2B or business smartphone review of the Samsung Galaxy S9. While Android and iOS operating systems dominate, this is also the case for business smartphones, and Samsung continues to improve the Galaxy smartphone series of devices to better meet business use and application needs. Below is a summary of my review of the Galaxy S9 based on a few months of use:
​
​Battery Life and Charging: I often have a number of apps running in the background like (Crowdfire, Twitter, Outlook Email and others) and generally do not have to charge my device until late in the evening, this gives me between 13 and 15 hours of business use daily before needing to charge. Now the exception is when I travel and when I am at a conference, since I tend to use the smartphone exclusively and use many more apps when I do not have my Samsung laptop open. Since business users, especially analysts, make many business calls throughout the day it is very hard to have poor battery life as conference calls, webinars, client calls are very vital to the operations of the business. Now, what makes the Samsung Galaxy S9 superior is that when you do plug in to charge, the fast charging process is extremely fast and allows you to get up and running very quickly.

Adopting innovative and smart infrastructure will enable businesses and government to enhance asset, infrastructure, and building performance. These physical structures are transforming into intelligence, cognitive, and predictive assets through existing and emerging technologies including Internet of Things, machine-to-machine communications, artificial intelligence, virtual reality, robotics, and deep learning. This spring’s, “Advancing Smart Infrastructure and IoT” IoT6 Exchange Summit brought together thought leaders, executives, advisory board members, and vendors to explore, learn, exchange best-in-class ideas, technology, solutions, and solve real issues around smart infrastructure. From retrofitting legacy assets and infrastructure to building smart and intelligence infrastructure from the ground up, this event presented hard hitting and actionable best-in-class learnings, and brought smart infrastructure ideas, projects, and use cases to life.  The event enlightened our attendees by capturing all the technology and innovation elements as the industry transition from unintelligent, static physical structures and assets to intelligence, learning, and digital structures and assets. DOWNLOAD THE FULL SUMMARY HERE.

Big news over the weekend for the wireless communications industry, as T-Mobile and Sprint announce a decision to merge but essentially T-Mobile is buying Sprint. The announcement came just before earnings calls for both companies, and was enlightened by joint CEOs taking to YouTube and social media channels to share the news and push the overall message of a bigger and better company leading the charge with 5G. A few details that we have gathered are shared below:

• Deal valued at $26.5B, and will create a combined company valued at $146B
• The T-Mobile branding remains, no word on what happens to the Sprint branding and sub-brands, No word on what happens to Sprint Wireline business
• John Legere remains as CEO of the joined companies, with Sprint CEO Marcelo Claure serving on the board of directors, and Mike Siervert takes over as President
• The main headquarters will remain in Bellevue, Washington with the Sprint campus acting as a secondary headquarters
• The new company will take executives from both companies to lead the charge, and no word on staff changes at this time. In a memo to T-Mobile employees, Legere wrote, "We’ll still be called T-Mobile, we’ll still be magenta, I’ll still be your leader, and we’ll continue to be customer obsessed!"
• Sprint gets a 4-year roaming agreement (they are paying fees to T-Mobile) with T-Mobile for LTE coverage in areas where their service is not up to par
  
• Softbank gets minority share at 27% with Deutsche Telekom holding 42% share with control over voting and the board
• Deal is pending regulatory approvals but they are expecting to close the 1H of 2019

​
​Based on Compass Intelligence tracker research, if we just look at the end of 2017 numbers and stats we collect and forecast, this will get T-Mobile to a combined 127M in connections which is 17M less than Verizon and 14M less than AT&T. What is substantial for the combined company is this...

• The NEW T-Mobile will shine in overall retail subscriber adds, having added 6.4M more than AT&T in 2017 alone.
• The NEW T-Mobile will dominated prepaid, maintaining about 30% of their overall retail subscriber base as prepaid customers and an estimated 24.2M more than Verizon and 14.3M more than AT&T.
• More work will need to be focused around two areas: (1) B2B - The combined company is estimated to have around 24M B2B subscribers, which is 30M less than Verizon and 24M less than AT&T (2) M2M and IoT Connections - compared to AT&T the NEW T-Mobile is extremely behind but only 428K connections behind Verizon.

​
From a 2017 revenue perspective, overall revenue is estimated to be about $1B less than AT&T and $2.5B less than Verizon. This new energy and push to take customers away from Verizon and AT&T will be invigorated with the new entity and Compass Intelligence expects for T-Mobile to place a heavy bet on pushing up the SMB market to take market share away on the B2B wireless side, and will continue to sway consumers to switch as the combined entity will have a larger footprint for the Un-Carrier strategy that has been extremely successful in the consumer sector. Some of the positive things the NEW T-Mobile can take from Sprint might include their go-to-market strategy on the B2B side and vertical segmentation expertise, as well as leveraging spectrum assets to lead in the industry. In addition, Sprint has a legacy knowledge base in prepaid and MVNO brands, public sector (public safety), and also youth and underserved consumers.

For more information regarding Compass Intelligence wireless tracking market data (both quarterly and annually), please click HERE to learn more or contact info@compassintelligence.com.

While IoT6 "Advancing Smart Infrastructure and IoT" Exchange Summit is fresh on the mind, we wanted to share a few highlights of the 2 day event in Ponte Vedra, Florida.

• Great attendees including thought leaders, IT managers, CXOs from Eaton, Volkswagon, American Airlines, multiple universities, smart lighting companies, and even manufacturers.
• Keynotes from Dell's Kirsten Billhardt, VANTIQ's Blaine Mathieu, Verizon's Sanjay Kumar, The Silent Intelligence's Daniel Obodovski, and SphericalAnalytic.io's Chris Rezendes...and of course Stephanie Atkinson to open up the conference
  • Topics ranged from data monetization, IoT best practices, enabling IoT for business transformation, sustainable governments, and next gen technologies for smart infrastructure solutions
• Fireside Chats with VANTIQ's Blaine Mathieu and Adam Stein to discuss real-time IoT applications, and Bob Egan lead another one between ClearBlade and NXP to discuss edge computing
• The panel discussions covered topics ranging from the future outlook, expert/analyst perspectives, and CXO perspectives, to securing end-point devices and compliance for smart infrastructure, asset tracking and fleet management.
• 1:1 Meetings and use case breakouts allowed for more in-depth discussions, deep dive into examples of live deployments in industry and government, and having these structured in the Agenda provides actionable follow up that will continue into this year
• Networking sessions included beautiful, scenic views of the ocean and resort amenities that was highlighted by sunset dinners, casino night, and superior meals and spirits!

Compass Intelligence will be preparing a executive summary of the conference and releasing it in the near future. Please be sure to participate as a sponsor or attendee this fall as we reconvene to concentrate on Smart Cities in Austin, TX at the Hyatt Lost Pines Resort and Spa, October 17-19th. Contact Stephanie to learn more!
www.iot6exchange.com

Today Kaazing announced DisasterAWARE ENTERPRISE™, a real-time risk and disaster preparedness platform for businesses across industry globally. I was honored to get a sneak peek by the Kaazing team (led by CEO Bob Miller) and learn more about how this supports and better prepares businesses. A disaster can mean downtime, loss of revenue, shipping delays, destroying of inventory, risk and loss of employees, and more. It is imperative that companies plan and prepare and have the right tools in place with real-time alerting and information that can be integrated with existing operational systems to not just react but to know in advance and have a strategic plan in place no matter where their assets are. While I sat through the audio/video conference I took a few notes that I believe were important to point out about DisasterAWARE ENTERPRISE:

• Data deliver is super fast! - 80% of the data is being delivered to the mobile devices for less than 2ms for something that was taking 200ms for a query
• Platform is very intuitive and full of capabilities
  • Visualize Hazards - dots represents hazards, monitored by PDC (Pacific Disaster Center (Univ of Hawaii)), avalanches, earthquakes, floods, tsunamis, mudslides, man-made hazards, and more
  • Familiar Tools - Uses Google Maps overlay
  • User friendly Icons - icons on left hand side allow for easy navigation and exploration
  • Layering of Information - users can look at different things like population density, lightening strikes, winds, velocity, global surface winds, wind speed (color coded) and users can bookmark locations
  • Social Sharing - social media icons are available and have feeds, a heat map of where tweets are coming from, types of tweets, searchable by type of disaster
  • Camera Icons - can turn on traffic cameras in areas and view multiple cameras, 
  • Further Data - other data available include historical data, business continuity, disaster recovery plans - ability to look at expired events, tropical cyclones for example (Maria)
  • Products - product are produced as a result of an event, response efforts broken down by geographies

Kaazing is targeting companies in insurance Companies, large supply chain companies (MNCs), logistics companies, and those large corporations who have remote offices.  Although Kazzing believes this platform and its disaster planning resources are industry agnostic, "Even more noteworthy, DisasterAWARE Enterprise is industry agnostic. It can be vertically integrated into the supply chain and logistics, and is well suited to protect a multitude of industries including travel, insurance, education, healthcare, utilities, finance, airports, mining, ports, retail, and other global enterprises," stated in the press release.

Data remains in silos in a digital environment and there is no real incentive to share it. This results in the hoarding of consumer data which emanates from Google, Facebook, Alibaba, and Baidu. Presently, artificial intelligence (AI) platforms give power to those few organizations that process a bulk of data. With sensors embedded in connected cars and devices across the IoT, there is the exponential rise in consumer data generated by these devices and stored in databases. A race has begun to get this data, which puts questions on privacy.
 
A blockchain is a decentralized, public digital ledger that keeps track of cryptocurrency transactions in a chronological order. Blockchains are considered disruptive to the financial world because no one person or body has complete control over the transactions. As a result, many consider this a more honest substitute for physical financial institutions like banks.
 
The blockchain technology protocol was first constructed by Satoshi Nakamoto. This technology works on the principle of transparency and the intent to distribute information to all parties concerned.
 
In this blockchain network, blocks of information are created for transactions which can be altered by anyone who has access to the blocks.
 
This technology protocol is now being used in the field of Artificial Intelligence. It allows AI engineers to create blocks of AI is open to other blocks of AI and work in tandem. While the technology itself is abstract right now, its potential could be parallel to that of the World Wide Web when it first started.
 
Blockchain allows users to share information and complete anonymous transactions. This technology is gaining hype. Blockchain offers an open, shared, decentralized data layer with data access to all stakeholders. These stakeholders include entities like city governments who use this technology to evaluate traffic patterns, car manufacturers who enhance driving experience, app developers who solve queries in real time, and healthcare providers who deliver personalized services on the basis of demographic profiles and usage patterns.
 
While blockchain has been trending only recently, most AI-savvy organizations have jumped into Blockchains to get consistency in their analytics. Professionals are curious to know what makes Blockchains so special, and therefore, enroll in an AI certification course to understand it.
 
The integration of Blockchain into AI
 
Not many people know the difference between artificial intelligence and machine learning. Despite this ambiguity, a lot is known and written about these two fields. The same, however, cannot be said for Blockchain. Surprisingly little is known about this field. Let’s understand the nature of Blockchain.
 

1. Immutability - This refers to the capability of AI to evaluate more data and models and thereby enhance the worth of these models. Deep learning certainly helps in this context; it’s the result of finding when and how, if provided a detailed dataset, to begin catch interactions along with latent variables.
   
2. Decentralized  -  With decentralized units, higher amounts of data can be processed and more efficient AI networks can be built. For example, when sharing the data amongst ecosystems or participants in a planet-scale ecosystem, such as the Web. Higher the data amount, the better the models could be.  
   
3. Transparency - Blockchain protocols provide a tamper resistance worldwide public registry. This results in testing data & models like intellectual property assets with the copyright claim. 

The most interesting part is we can have factual data that can’t be altered. Consider AI technology gets into Blockchains of data to get information, to discover patterns, and develop insights according to patterns.
 
Most predictions and patterns are more accurate as compared to the knowledge mining that AI performs which uses incomplete, missing data most times. Moreover, between Blockchain and AI, the fallible human elements are eliminated.
 
 Working examples explain its seamless potential
 
Here are the examples of real use cases that point out what Blockchain and AI can do together.

• Knowledge Mining: New learners like Neuromation deal in synthetic datasets to enable a business to master neural networks, laying the foundation for smarter AIs and pocket-friendly knowledge mining and sharing.

• Better Financial Services and Transactions: Using the data in Blockchains, AI can evaluate different types of loan products, demographics depending on those borrowing patterns while predicting products’ type that financial institutions offer.

• Proven Retail. AI can figure out similarities that may have been skipped through previous AI operations. For example, AI can determine that consumer transactions for guttering materials are higher in the summer. Then a big box home retailer will raise stock in those materials. Here Blockchain may show that the high demand for ladders that relate to purchases of guttering materials.

• Immigration. Blockchain technology is in use to validate citizenship in different regions, where birth records are not present.

 
Similarly, it can monitor the migration of people, groups, and the percentage of terrorist health issues depending on those movements. As AI gets this information, predictions become faster that help government agencies make better decisions regarding immigration policies and health concerns.
 
Important Blockchains benefits
 
The main concern of Artificial Intelligence is with understanding the hidden patterns in Big Data resulting in autonomous machines whereas Blockchains have the primary concern with accurate records management, security, and relevance. Data sharing is the first benefit of Blockchain for AI.
 
As AI is associated with data, Blockchain becomes a gateway that leads to secure data transfer over the internet. A lot of processing time is what it saves between the points where the data is evolved and evaluated. Self-operating devices have autonomous nature, therefore, needs secure inter-device communication, one of the other problems that Blockchains can solve.
​
Moreover, Blockchains ensure that the data authentication on which AI models depend. The nature of machine learning models is “Trash In, Trash Out” - if there is any compromise over data used to develop the model, then the model results won’t be beneficial.
 
Conclusion:
 
Blockchain technology delivers relevant data that has been checked by various people prior to its movement into a block. It cannot be changed and is available publicly. It is highly relevant than data that is delivered on unproven platforms with embedded errors.
 
Blockchain offers a trustworthy information source to retailers, governments, businesses, financial institutions, non-profits, health and educational organizations, scientific researchers thus enabling informed decision making.

AT&T adds 6.7M connections in 2017 including IoT, while T-Mobile reigns in Subscriber Adds

All four carriers have finished up their earnings calls, and Compass Intelligence just completed the final assessment of Q4 2017 and the entire 2017 analysis. In addition, Compass Intelligence evaluated the comparisons to previous quarters and year ending 2016 to 2017 in terms of improvements and declines. We do this each quarter to understand the subscriber and share changes, as well as evaluate the key trends taking place in the wireless industry for both consumer and B2B.  We have been tracking the quarterly metrics since 2007. Some metrics are our own internal modeling and estimates, as the market does not report in all categories.  A snapshot of Q4 2017 is below.
​
Compass Intelligence compared last quarter’s results to this quarter to show which metrics showed improvement over others (denoted by + or -). 

Below are additional thoughts and insights based on the quarter and annual performance:

• Summary:
  • Q4 2017 experienced the most additions of connections for 2017, while Q3 experienced the highest overall service revenues compared to other quarters
  • The Q4 2017 quarter ended adding 6.6M new connections QoQ (includes IoT and mobile subscribers), which is 12.9M added for the entire year.
  • Retail Subscribers for the Top 4 carriers reached 309M, or an addition of 6M added for the whole year
  • While Verizon maintained the lowest churn for the year at an average of 1.02% in 2017 compared to .985% averaged in 2016, AT&T followed with an average churn for 2017 at 1.08% (same as in 2016)
  • A total of 3.8M tablets were activated for the entire year (2017), which is a decline from 2016 as many rely on Wi-Fi for connectivity and even use their phones as hotspots
  • Verizon ended the year with 35% market share, followed by AT&T with 34%, T-Mobile with 18%, and Sprint with remaining (market shared based on number of connections including subscribers and connected devices/IoT)
  • AT&T leveraged its growth in IoT connections in 2017, while T-Mobile gained the most retail subscribers with roughly 4.5M added in 2017 (twice more than the next largest carrier additions, Verizon) (Note: T-Mobile made a decision to remove Lifeline subscribers from its wholesale connections in Q2 2017, which impacted overall Total Connections trends for T-Mobile)

​As shown above, overall the industry added an estimated 12.9M connections in 2017 compared to 21.5M connections in 2016, which represents a 3.1% change from 2016. While Verizon ended the year with the most connections at 144.4M connections, T-Mobile lead overall retail subscriber adds for the year, adding over 4.4M subscribers in 2017. AT&T’s growth was primarily driven by IoT connections, adding an estimated 7.4M connected device connections in 2017 (2M more than adds in 2016). Sprint had its own success story returning to positive net adds for the year, adding 488K in Q4 alone.

For access to our B2B market research and tracking services, click here.

Today marks an important time for women across the world as we celebrate International Women's Day during a time when brave women are speaking out about gender parity, coming together to fight against past assault issues, and focusing on lifting each other up in a supportive, empowered, and celebrated fashion. Being in the tech world all my life, I have experienced a host of issues with gender disparity in the workplace, and that was a major driver for me to start and run my own business. But today we celebrate women around the world as they pave the way for the younger generation to focus on STEM education, data science, coding, and technology. We celebrate those women making such a strong impact in the IoT sector, being visionaries and futurists in connecting, digitizing, and transforming companies across the globe. Below are a few of my favorite quotes from 4 females in the IoT and Emerging Tech Sectors...please help me celebrate women in tech on this special day!

 Sarah Cooper
GM IoT Solutions at Amazon Web Services
​
"I think we haven't seen [the growth of ambient intelligence] because of this ecosystem problem of how do we then distribute that additive value, how can we distribute that back to the vendors?" - Light Reading

Joyce Mullen
President, Global Channel, OEM and IOT Solutions at Dell EMC

​"We have to figure out how to evolve our training to address those solution sets that we've chosen as the starting point. IoT (Internet of Things)  is the most obvious and glaring in my mind. That is such a sausage-making exercise right now for any type of solution to be put in place." - CRN.com

Padmasree Warrior
CEO NIO U.S

​"Learning means ... sitting down with other people from different domains. Learning means discovering things, learning means reading things, learning means exposing yourself, pushing yourself [to do things] that you know people will tell you you can't do." - CNBC.com

Tamara McCleary
CEO Thulium.co

"​It’s similarly plausible that while the US and China produce technologies quickest, the first truly considered, ethically-sound and beneficial implementations could come from the European power sector." - Gigabit Magazine

Written By Stephanie Atkinson, CEO of Compass Intelligence

Enterprise Threat Modeling Provides the Needed Real-Time, Dynamic Perspective
by Archie Agarwal, CISSP
CEO & Founder
ThreatModeler Software, Inc

Cyber attacks and the associated risks are considered the number one concern by business leaders in advanced economies around the world. Leaders also perceive risks associated with cyber attacks as being the most likely risks to intensify in 2018.[1] The identified attempts of attackers to locate and compromise system vulnerabilities rose a staggering 82% through the last half of 2017 alone,[2] and the trending increase in new, advanced threats shows no signs of abatement. New exploit kits readily available on the dark web such as Sundown, RIG, and Neutrino allow even armature attackers to automate vulnerability searches, use advanced technologies to conceal the harvest of information, distribute ransomware or other malware payloads, or push persistent means to lure unsuspecting or unwary internet users.

Two-thirds of enterprises report the evolving threat landscape tops their list of business risks, yet only 20% of survey respondents are highly confident that their organization can manage and mitigate these risks.[3]

At issue is more than the cost and reputational harm of a data breach. At worst a data breach presents a $50 million liability to a company with more than $1 billion in revenue – a material matter for the annual report, but nothing that cannot be overcome by a mature enterprise in 12 to 18 months. Equifax shares, for example, fell 34% in value immediately following their September 2017 announcement of a massive data breach, resulting in a loss of market value of almost $5.5 billion. However, in just five months shares in Equifax are trading 23% higher, and the company’s market value has rebounded by 43%.

This is not to say, as some have suggested,[4] that it may not be worthwhile to recognize security events between reporting periods. On the contrary, the ability of large organizations to bounce back after a data breach is indicative only of the resiliency and resources that went into making a large enterprise. Furthermore, a breach of confidential consumer information, while potentially resulting in material reputational damage to the breached organization and substantial collateral damage collectively for the individuals connected with the breached information, is not the most significant cyber risk faced by businesses.

The bulk of a company’s value today – 80% or more – is derived from intangible assets.[5] For companies on the S&P 500, intangible assets contribute up to 90% of market value. The point is, while public outrage, media attention, and hard-hitting regulations like the soon-to-be-enforced GDPR focus attention on the beaches of customer information, there is much more at stake. The loss of proprietary intellectual property, pre-published financials, or internal communiqués to a competitor through cyber espionage, even if eventually detected and legally defended, can materially harm a company or jeopardize its status as a going concern. Despite what is at stake, nearly three-quarters of organizations are “cyber novices,” having neither the strategy nor the execution to mitigate the risk of a potential or realized cyber-attack.

Interestingly, though, even if an organization is ranked among the elite 11% “cyber-experts,” they are just as likely to report a security incident as novice-level organizations. Apparently, attackers armed with automated exploit kits are not easily deterred by the number of guards at the gate or the defensive technology that may be in place. Increased spending alone on security technologies does not produce a more secure cyber environment.

In response, many business leaders, most notably from within the cyber insurance industry, are calling for better quantification of organizations’ cyber-exposure. The challenge, however, with which insurance providers and their customers struggle, is that quantifying cyber risk is fundamentally different from quantifying other types of risks.

Unlike traditional risk-assessment environments, an organization’s cyber environment is dynamic. Data moves to and fro throughout the office, even around the world, on a regular basis. The data is continuously changing, increasing, and being used to create new data. New applications are continually introduced. Cloud-based deployment environments expand and contract on demand. The number of IoT and mobile devices connected to the organization’s IT system continuously increases and often adds unowned and uncontrolled attack surface exposure. Moreover, organizations are increasingly bringing online industrial control and other cyber-physical systems to digitally operate everything from manufacturing plant equipment to office air conditioners. Executives and insurers cannot quantify an organization’s cyber-exposure unless and until they understand their threat portfolio and attacker population across the entire cyber ecosystem.

Security practitioners have attempted to understand the threats and attack patterns relevant to new applications through threat mapping for almost two decades. Threat mapping provides generalized understanding based on data flow diagrams of how individual assets can be attacked through the application being analyzed. Because it tends to be a slow, resource-intensive activity, however, the scope of what an organization can realistically investigate with threat mapping is annually limited to a few critical and high-risk applications in isolation – barely scratching the even the tip of an enterprise’s digital ecosystem. The result is that organizations can only attempt quantification of their cyber risk exposure based on static framework audits and analysis of cyber event histories. Doing so is about as expedient as navigating your commute to work while only looking in your rearview mirror. The mirror has its necessary function, but you need to be forward-looking to quantify and manage risk effectively.

Organizations need to develop a comprehensive, rigorous, structured set of security policies and processes that drive security end-to-end – before the incident or breach happens. The only way to achieve this within a dynamic environment is with enterprise threat modeling. Enterprise threat modeling analyzes the overall security risk posture across the full IT ecosystem – including the highly complex, multi-phased attack paths employed by today’s APT actors. Whereas threat mapping scratches the tip of the IT security iceberg, enterprise threat modeling allows organizational stakeholders to collaboratively hold the iceberg in their hands and view it from multiple perspectives. Enterprise threat modeling provides the “big picture,” in real-time, of the organization’s dynamic security posture. Automated enterprise threat modeling does for executives and security leaders what looking out the front window does for commuters on their way to work – to see what is coming, to quantify the risks, and to take the appropriate action before an event occurs.

Contact:
Brian Beyst
Senior Director of Marketing
ThreatModeler Software, Inc
101 Hudson St
Jersey City, NJ 07302
Phone: +1-507-251-0851
bbeyst@threatmodeler