8 Best application examples for blockchain in the US Navy (or your organization) – Part 2

https://shocard.com/shobadge/

Part 2

Moving from Tactical  to Operational: Contained Blockchain Deployments

 

In Part 1, we explored the building blocks of blockchain – bitcoin and smart contracts. These top level basics of blockchain work quickly toward more complex operations. Step by step block chain applications are progressing right now in today’s industries. It’s as easy as 1-2-3D.

Going 3D

As the tactical is utilizing bitcoin and smart contracts to execute stand-alone functions for test and evaluation, the next step is to pull the isolated applications into a third dimension, kinda like the third semester of calculus.  For the US Navy, that opportunity could be implementation with Additive Manufacturing. Here’s why.

http://www.4erevolution.com/wp-content/uploads/2016/11/Cubichain-flowchart.png

http://www.4erevolution.com/wp-content/uploads/2016/11/Cubichain-flowchart.png

Nascent Technology.

Although 3D Printing was developed in the 1980s, the feasibility of metalworking for parts such as nuts and bolts didn’t mature until the 2010s. Thus the capability being explored is founded in practice and yet still molding (har har) into full application – in regard to the grand scale of spare parts that the US Navy demands. Because of the newness, the technology and its deployment are still pliable.

Bounded Issue.

Spare parts are a significant contribution and yet a contained subset of Navy needs for its mission. Although the traditional supply chain may be cumbersome and expensive, it works and provides a stable backup for production.

Appropriate Application.

3D printing is a developing technology itself that is fundamentally digital. Since additive manufacturing begins digitally and executes digitally, utilizing blockchain enhances the process by simultaneously replicating the team effort to the distributed ledger. Blockchain is adding to the system, not replacing it.

In the summer of 2017, the Navy actually announced plans to use blockchain for additive manufacturing. Numerous US government organizations such as the Center for Disease Control, Department of Homeland Security, Department of State, and Office of Personnel Management are also investigating the possibilities of blockchain in their missions.

Coming Together

This graphic illustrates the interconnected capabilities of blockchain while still keeping the basic concepts in common buckets..

https://www.devteam.space/blog/the-rise-and-rise-of-blockchain-as-a-service/

https://www.devteam.space/blog/the-rise-and-rise-of-blockchain-as-a-service/

Additive manufacturing itself is seen as a means to reduce costs and enhance the production cycle in both time and quality.  With smart contracts, the additional benefit is simultaneous, irreversible duplication of the production cycle as it lives. All members of the process – start to finish – are active and aware of the function transactions.  These members are the selected distributed network of nodes that are integral to the process: creators, engineers, users, legal, accounting and poignant chain of command. Because of the inherent sequential iteration foundation of blockchain, every version of the product – success, failure & in-between – is captured for the network. So mistakes are captured for remediation as well as historical reference functionally or administratively.

While the current means for supply aren’t going away, blockchain provides opportunity to further expand the benefits of smart contracts while minimizing the risk.

APPLICATION 3: expand testing smart contracts for consumption through the Additive Manufacturing deployment

 

Identity Management

“What’s in a name? That which we call a rose by any other name would smell as sweet.” – Shakespeare

As we move further into operational, identity management is another subset that is already in practice in industry.  In a world of biomarkers and data exhaust, an individual can be identified by so much more than a name or a number. Using thumbprints or retinal scans never became as common as future-casts predicted, and even identification cards are losing their power.  For example, when is the last time someone checked your ID card when paying with a credit card? The card actually says “not valid until signed,” but is the signature on the back verification for the vendor or opportunity for a forger? A new practice also allows for no signature of the receipt for purchases under $50, which indicates a proven algorithm of risk and return for chasing fraud according to a threshold.  Credit agencies have many more mitigation strategies that subjugate the need to identify the user.

 

Today

Blockchain Identity Management (IDM) has not been accepted as common practice as yet.  At this stage, developers are still exploring the technology and with the significant threat of information breeches, it is understandable financial institutions are leading the way. The potential though is being carried in real currency.  Blockchain IDM startup Selfkey began its Initial Coin Offering (ICO) with the intent of selling a limited supply through the end of the month.  They closed sales in 11 minutes when they reached over $21 million in investment. Last June, Civic raised $33 million through ICO, again closing the sales well ahead of schedule.

Another strong demand signal is creating a global identity standard, establishing a common practice for personal identification worldwide regardless of country of origin. Several startups are utilizing bitcoin, blockchain, open and secure networks to meet the demand signal of digital containment.

https://shocard.com/shobadge/

The blockchain holds no PII data, only verification signatures that cannot be reverse engineered.

 

 

 

https://shocard.com/shobadge/

Futurecast

Since blockchain is an ongoing accumulation of data blocks in a chain, think of a person’s identification that way.  The person doesn’t change so much as their circumstances. Blockchain is used for identifying diamonds and high-end wines as they travel from point of origin to sales floor. The item itself doesn’t change; its journey defines its identity. Its value is certified by the steps it takes, which are captured as blocks in a chain.  Only when the chain is broken or corrupted, then the item not only becomes scrutinized but also the sequence of events can be evaluated for interpretation and judgment.

The credit card company knows it is you more or less when you charge and the down side risk is minimal compared to the cost of deeper certainty. Individuals with security clearances by and large keep to the trust endowed. With blockchain identification, the organization and all the individuals who are trustworthy benefit when a single trustee breaking the chain can be identified immediately.

Blockchain Identity Management is a good operational application because it does not replace existing trust systems in place. The technology can be “bolted on” to a test unit for determining best practices.  The bounded process can then be readily implemented and replicated. Identity management is ideal for blockchain implementation because the ongoing issues of personal identification risk are rising. A light bulb is needed because better candles are not sufficient to hinder hacking.

 

APPLICATION 4: develop identification blockchains for access to classified information

UP NEXT:  8 Blockchain Applications for the US Navy (or your organization): PART 3, Expanding Operational: Blockchain Deployments for Impact


 

Show Your Tatas! Big Data on Big Boobs, Bras & Breast Cancer

Big Data Takes on Big (Boob) Problems

Big Data application comes in many shapes and sizes and the Big Data Bra is Big Data wrapped in the silk and latex of lingerie.

It starts with a simple problem.

We have come a long way baby from corsets and elastic superstructures. The width and breadth of materials and configurations is overwhelming today and surpassed only by the running shoe industry in the utilitarian fashion spectrum.

Yet bras still don’t fit well. For those who “need” to wear them, they pinch and sag and ride up your back. You push and pull to pack ‘em in and in return they pooch and groan to comply. The straps spend a lifetime slowly paving a permanent groove over the shoulder. At the end of the day, within the privacy of the house, you pop the straining band – freedom!

Open the bra drawer on the dresser and the volume and variety (2 Vs) are apparent. There’s a bra for every occasion: bras for sweaters or for t-shirts or racer back or the all-day-at-work ones. The padded, the push-ups and the breast minimizers. Going to the gym or hitting the trail is a whole different world altogether, with sports bras equipped in extraordinary configurations to look good somehow while keeping everything from exploding.

Then there’s a whole undergarment wardrobe established just for after dark: the trying-to-be-sexy bra, the one bra that goes with THAT dress bra (the dress is sssoooo cute but only one bra works with it), and the worst ever compromise – the strapless bra. These all fall in the genre of i-can-last-x-hours at the restaurant/dinner party/gala event. There are pads and patches to replace bras and yes, in a pinch, the old school – duct tape.

One Size Does Not Fit All      

And neither does band width and cup. Travel to any department store lingerie section and you’ll find a world of bra selection. Unless you don’t really need one, it’s not about size and color. You want what looks and feels great. Although you want something pretty, it’s about fit and form. This is a perfect example of lots of selection but not true fit.

So you spend as long as you can stand in the lingerie section. Like the 20 year old dating strategy, you try on bra after bra to find the perfect match, or at least one that will work for a while. It’s a simple affair then but as time drags on (downward I mean), it gets harder to meet one you like. You know it may fit in the store and “hold much promise” but one wash later and it is on the path unfortunately to break down. Keeping it clean means delicate washes and special care but it’s going to unravel on you sooner than you like.

So how about flipping the market from push to pull? A single customer doesn’t need all that selection. She needs The One(s) that fit her. Wouldn’t the manufacturer and retailer want to sell her The One(s) without holding the inventory of racks of choices and piles of discards? Instead of creating a huge variety of bras that consumers can squeeze into, how about starting with the customer and tailoring the selection to her exact dimensions?

“3D printing is creating everything from cars to human tissue. Facial recognition software commonly creates 3d renderings from its algorithms.Facial recognition technology captures data form the contours of a person’s face and then computes the ratios between each feature. Since no face is exactly the same, each person would generate a unique data set based on the shape, size, and location of their features. This mathematical output can be compared and sorted for matching and identification purposes or to track a person’s identity.”

http://blog.m2sys.com/guest-blog-posts/beyond-science-fiction-facial-recognition-software-transforms-airport-security/

In a world of 3D printing and people recognition software, you should be able to take some pics and make a bra – 10 bras – that specifically fit the pic.

That’s where Big Data comes in.

My Big Data Bra begins with uploading personal pictures to the Volume, Variety and Velocity of data from Victoria’s Secret or Bali or Warner or Free People or Maidenform or Wacoal. They design and manufacture a bra – a suite of bras if they’re good – and send them to me, not the store.  They send me sales suggestions on replacements. I send them back my battle worn discards, which they computer analyze for fatigue to find the next best thing – for me – using the millions of data points around me. I can send new pictures to show adapting to life’s gravity effect or cosmetic repair thereof and they use the feedback for new bras. The cycle continues.

Nice Tata Thought, but How Does This Solve Big Problems with Big Data?

This consumerism creates a huge non-medical database of biometrics. These geo-tagged, anomyzed sources are deposited in data lakes with other data associations. It creates a new lens for researching breast cancer. Several breast cancer studies have already linked larger breasts to increased risk of cancer but the correlations are only suggestions.

More data would create more patterns and new opportunities. In one capability, the information is utilized by huge research organizations, using larger resources in order to view the Big(ger) picture.

Another angle is third party specialists create ways to analyze a personal signature against other Big Data sources – location, transactional, lifestyle, etc. – to assimilate breast cancer risk factors unique to that person. Third party providers could also suggest products and services to enhance breast life choices. There could be an app for using the pictures to tap into other big data resources for your overall health.

Further outside the box

Now blow this concept out of the bra. Whole body scans could do the same for total body health by incorporating pictures into your Big Data Medical Record. Providers use them as part of a holistic view of your health. Apps analysis helps assess your strengths and weaknesses. Big Data derives suggestions for effective and very personal results.

Like your cell phone traffic app provides a comprehensive picture of traffic for everyone, it also provides specific information personally important to YOU (like where u are).

We live in a global collective. Now is only the beginning of its documentation. Big Data is the ability to utilize those billions of millions of data points. Let’s use Big Data to solve Big Problems.

Ain’t Talkin’ ‘Bout Love and The Edge of the Internet of Things

https://techcrunch.com/2017/08/03/edge-computing-could-push-the-cloud-to-the-fringe/

Aint Talkin Bout Love and The Edge of the Internet of Things

 

I’ve been to the edge

And there I stood and looked down

You know I lost a lot of friends there, baby

I got no time to mess around.

  • – Van Halen, Ain’t Talkin’ ‘Bout Love

 

Ah … nothing like 1978 classic rock lyrics about getting/giving an STD to start off discussion on emerging technology.

The Edge or Edge computing is an important tenet in understanding the Internet of Things (IoT).  Wherein you may never reach the end of the internet, you can actually see the edge of the Internet of Things.  “Things” or sensors exist everywhere – anywhere in a process or across multiple processes – but at some point there is an end of the line.  From The Edge, sensors stand and look down … and out and around at the physical world. Because they are at the Edge, these nodes can be the furthest extent from the people and processes that are interested in the information or they could be right there where they are needed.  Thus this can be where you gain or lose the best data (friends). This is where measurements are real time… when there’s “no time to mess around”. The Edge is current discussion on security as well, keeping the systems and processes free from disease and evildoers. The Edge is an important feature in building and utilizing IoT.  

 

For Example

To explain how the Edge works, let’s go back to an old school intrusion detection system and smoke/fire alarm (I used this in my IoT Connections blog post.) Pre-Internet, intrusion detection or smoke/fire alarm systems had various sensors hard-wired into place to determine whether the desirable conditions (no fire or intruders) were being met.  Smoke and fire devices triggered alarms for heat or chemical substances within a physical building.  Burglar alarms were usually a circuit that once broken sounded the alarm.  For both, the alarm could be sounds or lights that were experienced just by anyone there or they could be connected via land lines to other players that could call emergency services.

When the sensors are triggered, the alarm sounds there at The Edge.  Anyone in the building who is aware of the alarm understands the dangers and has the ability to make decisions from that information, such as calling the police or fire department or taking others actions such as evacuations or defense procedures.  If the sensors are connected to a monitoring service, the responders are trained and ready to act appropriately.  Perhaps the system may be able to notify the emergency services directly.  That is Cloud decision space.

With the pervasiveness of the Internet and the autonomy of the design, you can easily understand the most preferable choice – an instantaneous, specific and desirable response to an emergent situation.  Thus the IoT has grown exponentially, leveraging the combination of ubiquitous sensors (active and passive, deliberate and advantageous) and omnipresent Cloud.  However, this popularity is changing.

http://www.businessinsider.com/internet-of-things-cloud-computing-2016-10

Keeping it Local

So Why NOT Use the Cloud?

For the 15 years that IoT has been growing, it has crawled the Internet as a natural progression.  Utilizing the ubiquity and ease of the Cloud made undeniable leverage of current operations and projected expansion.  Afterall, so far the Cloud is an amorphous, expanding universe that has served our needs.  We haven’t reached the end of the internet, so why not continue mining a perceived inexhaustible resource? However, recent developments have begun shifting the processing of the sensors back to The Edge for decision making.  Four reasons have driven it back.

 

Cost. The cost of sensors continues to drop, and the capabilities of those sensors are increasing.  Subsequently, more data with more fidelity is possible at multiple touch points.  Processing ALL the sensors in the cloud derives a resource tax.  Simply, you can buy more sensors by saving the cost of connecting to the Internet.  Or you can even more simply spend less money.

 

Security.  Proprietary or personal information is risked with exposure to The Cloud.  Keeping the information local to the sensors for decision at the source can be more effective as well as provide better security.  The Edge sensors still need safe-keeping but the damage control is more easily prevented or contained.

 

Design.  Just because the Cloud is there doesn’t mean you need to use it.  KISS.  The Cloud doesn’t necessarily fulfill the mission of the system created.  The Cloud is actually getting pretty crowded, and for now, this point in time, keeping the game locally may be in the best interest of the system.  Also, capability has developed to collect data from multiple sensors but interested parties have different access for different needs.

 

Speed.  “Instantaneous” is highly measurable now.  The meer fractional computation distribution of data still may not be fast enough.  For example, autonomous driving cars need Edge computing because the criticality of data for safe driving decision simply is too fast to zoom out and back to the Cloud.

 

Farm to Table

A current application of Edge computing is sensors planted with crops.  These nodes constantly provide feedback as to the soil’s properties, such as moisture content, mineral composition, and density.  The automated watering systems then deploy precise amounts meter by meter, not acre by acre, determined by real time monitoring.  Cost savings are realized in both water and fertilizer consumption.  The harvest is more bountiful and The Edge is more likely cheaper than utilizing a Cloud structure.

Ain’t Talkin’ ‘Bout Love

But The Edge is where sensors are beginning to do more of the heavy lifting of data processing and decision making – for now.  Technology will evolve and we will rock and roll with it. Be careful though because just as with The Cloud, you wouldn’t want to catch a virus or malicious attack any more than you would give one.  Always practice safe sensor deployment.  Like the 80s, all trends don’t die; they just come back around.

 

Previous post on IoT: IoT Connections

Next up:  PIoT vs IIoT

 

Look out for more than bones in the fish you’re eating … batteries included

With the Internet came the ability for computers worldwide to connect regardless of race, creed or country.  As the Internet evolves into the Internet of Things (IoT), more and more sensors – not just computers – connect to further enhance business, economics and life in general.  Food for example comes from around the globe.  Brazil provides 30%, Florida 15% and China coming in a close third.  How do you know it’s fresh?

Shipping fresh produce or fresh fish or fresh anything requires controlling environmental conditions that keep it safe for consumption at the table.  Originally it was refrigerated by some means deemed sufficient and let the eater beware.  Greater care was placed in the process by measuring the temperature and humidity of the container.  Eventually that meter was monitored.

Today, any safety conscience food provider has the means via the Internet of Things (IoT) to monitor the container wherever it is in the world from wherever the company is in the world in real time.  Giovanni Salvatore and ETH Zurich have taken even that capability a step further by developing a sensor that actually attaches to the fish or produce itself.  And it’s okay to eat it!  The sensor is far thinner than a human hair (eck, don’t think of how that became a measure.)  Not only is it edible, but it contains magnesium, which is good for you – in the right amounts.

It’s not quite in a market near you though.  The sensors still require a power source so the battery attached is a bit self-defeating at this point.  No worries though.  Several sensors in other industries have already been developed that don’t require power.  It won’t be long before you’ll checking the gills for a freshness date!

 

 

Source: https://www.engadget.com/2017/09/29/super-thin-edible-sensors-monitor-food-temperature/

O’Reilly Media’s Friday Freebie – 3D Printing Primer

Get your free copy by clicking HERE.

Demystify the field of 3D printing, by outlining the strengths and liabilities of the different types of processes that are currently available.

Click on the hyperlink text to get your free copy!

Whether you know them as “rapid prototyping,” “additive manufacturing,” or some other buzzword, the processes, technologies, and tools of 3D printing are developing at such a rapid pace that it’s easy to be overwhelmed or confused by the ever-increasing range of options. This report helps demystify the field of 3D printing, by outlining the strengths and liabilities of the different types of processes that are currently available, along with an indication of advancements to be on the lookout for in the near future.
Because there are many ways to “3D print” an object, this report focuses on distinctions between the various methods (including lithography-based methods, robot-controlled extrusion methods, powder-bed methods, and a few more exotic processes), providing examples of each process in the commercial, consumer, and DIY/open source markets. Rather than promote or endorse a particular make or model of 3D printer (or type of printer), the purpose of this survey is to help identify the right type of printer for particular uses, narrowing the field to a more manageable number of candidates. You’ll also learn about concerns and limitations that apply to all methods,

David Saint John

David Saint John

Dr. David B. Saint John is a researcher, educator, and technophile currently performing post-doctoral research in additive manufacturing methods at the Penn State Center for Innovative Materials Processing through Direct Digital Deposition (CIMP-3D). He has guided students and faculty in the construction of over 30 open source 3D printers and the repair of many commercial 3D printing systems, and he is currently assisting industry groups in their adoption/application of methods for the additive manufacturing of metal components. His broader interests include transformative technologies beyond additive manufacturing including Nanotechnology and Cryptocurrency (e.g. Bitcoin).

 

This report helps demystify the field of 3D printing, by outlining the strengths and liabilities of the different types of processes that are currently available, along with an indication of advancements to be on the lookout for in the near future.

Demystify the field of 3D printing, by outlining the strengths and liabilities of the different types of processes that are currently available.

Big Data & Your Vote: Did Trump Change Your Mind?

Two summers before the 2016 US Presidential election, I was sitting around a bonfire in the wilds of Kenya, lingering in the peace that comes from spending the day amongst the extraordinary wildlife of safari (that’s ordinary for Africa). An intimate gathering of around 15 guests from all continents, the conversation was friendly and centered on the day’s site seeing. Eventually though it meandered into the typical conversationalist vernacular: who you are, where are you from and what do you do.

There was an extended pause as we all gazed into the fire, reminiscing on elephants, lions, and miles of wildebeest trekking the Mara. I was dreamily wondering about the potential of the universe when an unexpected verbal volley shot across the flames.

“So what do you think about Donald Trump becoming President?”  Like a grandmother’s awkward question about a pregnant member at the holiday family dinner table, heads turned and all eyes rolled toward to me, the sole American representative.

I wish I could say I easily conjured an interesting and insightful and perhaps even clever reply to demonstrate my thorough comprehension of American politics but honestly the thought in my mind a year before primaries was “… Donald Trump is running for President?”

With Trump’s victory in the history books, it seems pretty obvious now, but until Election Day, Hillary Clinton seemed to be walking away with the prize. As for me on safari a year plus before the election, I had been buried deep in personal and professional malaise for several months. I hadn’t given any thought to the election; those games would begin without me. Obviously, other people – from around the world – were looking into United States politics. At the moment, they were looking at me.

My mind went through several iterations of perspective thoughts, but each was rejected for lack of intelligence or wit. I gave a public-affairs response along the lines that at this point, many people put their hat in the ring early for a variety of reasons. Internally I thought that Trump had a very clever plan to position himself for something more viable to his operations. He was stumping for a cause or a better deal.
[thirstylink linkid=”1602″ linktext=”” class=”thirstylink” title=”Big Data coffee mug”]
Oddly enough, he ended up with becoming President (which means the causes and deals are still a fait accompli).

Elections as the Founding Fathers saw them

Selecting the Executive Officer for the United States was a point of contention for the Constitutional Convention that met in 1787 to further define the Articles of Confederation that had originally sustained the thirteen colonies. As much as the delegates wanted the government to be of the people, they had their doubts as to how much they really trusted the average person capable of making a good decision. They also contended with exactly who counted, women and minorities did not, and the less populous southern states wanted equal representation in electing the chief executive officer. The Federalist Papers argued the merits of the proposed Constitution and specifically #68, arguing how the President should be determined. The compromise is Article II of the Constitution, which spells out the Electoral voting process.

The result is the popular vote tips the hand of the Electoral College. An interesting arrangement, it nonetheless has stood the test of time. Mostly, the people vote the country’s conscious, but on those times where it’s a little dicey, the safe stop comes into play.

Evolution of elections

This year was not the first year that electoral vote did not match the popular vote.   Some can recall the famous “hanging chad” recount in Florida between Al Gore and elected President George W. Bush. The Supreme Court had to step in on that one as the very essence of how a vote is counted became questionable itself.

A hundred years previous to that was the 1876 centennial race between Rutherford B Hayes and Samuel Tilden. This – the most contentious race in US history – was settled by the famous (or infamous according to some) Compromise of 1877, which removed the last occupying soldiers in the southern states to end the Reconstruction Era. It also recorded the greatest voter turnout in US history.

The Information Age – This or That

Coming back to the more recent elections, reaching out electronically via the Internet came to play for President Obama’s campaign, which is credited with the first victory utilizing social media. His team developed virtual grass roots capability, breaking ground with the now common practice of A/B testing. The website experts at Optimizely derived the magic that would test six media options and four call-to-action buttons. These web page features examined the subtle differences to check for conversion rates.

 

learnmore-300x76-1joinusnow-300x76signup-300x76signupnow-300x76

The media was video or picture, with President Obama by himself or with family. The four choices for “call to action” buttons seem the same, but what is the difference?

The famous “Combination 11” won. 

The winning variation had a sign-up rate of 11.6%. The original page had a sign-up rate of 8.26%. That’s an improvement of 40.6% in sign-up rate. What does an improvement of 40.6% translate into?

Well, if you assume this improvement stayed roughly consistent through the rest of the campaign, then we can look at the total numbers at the end of the campaign and determine the difference this one experiment had. Roughly 10 million people signed up on the splash page during the campaign. If we hadn’t run this experiment and just stuck with the original page that number would be closer to 7,120,000 signups. That’s a difference of 2,880,000 email addresses.

Sending email to people who signed up on our splash page and asking them to volunteer typically converted 10% of them into volunteers. That means an additional 2,880,000 email addresses translated into 288,000 more volunteers.

Each email address that was submitted through our splash page ended up donating an average of $21 during the length of the campaign. The additional 2,880,000 email addresses on our email list translated into an additional $60 million in donations.

https://blog.optimizely.com/2010/11/29/how-obama-raised-60-million-by-running-a-simple-experiment/ boldfaced added for emphasis

Many of us wouldn’t consider 8.26% significantly less than 11.6%, but this simplification exemplifies the extrapolation of data capability when the numbers become Big.

One of the big takeaways that Optimizely upholds is the “knowledgable” staff putting together the website instinctively felt certain features would be the top performers. They were wrong. They learned to accept that data has results that “trump” their gut.

Lessons Learned

  1. Every visitor to your website is an opportunity. Take advantage of that opportunity through website optimization and A/B testing.
  2. Question assumptions. Everyone on the campaign loved the videos. All the videos ended up doing worse than all the images. We would have never known had we not questioned our assumptions.
  3. Experiment early and often. We ran this experiment in December of 2007 and reaped the benefits for the rest of the campaign. Because this first experiment proved to be so effective we continued to run dozens of experiments across the entire website throughout the campaign.

https://blog.optimizely.com/2010/11/29/how-obama-raised-60-million-by-running-a-simple-experiment/

Speaking of Trumping

President Elect Trump was noted a great deal for controversy and one of his earlier campaign comments badmouthed Big Data; however, in the waning months of the run he turned to his son-in-law Jared Kushner to spin the magic of Big Data. (Trump since then has appointed Jared Kushner Senior White House Advisor.) Jared went to a Texas based marketing firm Cambridge Analytica. Untested in political waters, the company instinct was less of an influence. They were using the data. Ah yes, Big Data.

In comparison, the 24 Obama message small data combinations were countable. The Trump messaging system incorporated 4,000 messages read by over 1.5 billion people. Whereas the Obama campaign converted traffic arriving at the campaign website, the Big Data of Trump crawled all of Twitter, Snapchat, Instagram, Pandora and more to pick just the right ad to influence … you.

Like traditional politics, if your mind was made up, no ad would likely change it, but for the swing votes, and states, and Electoral College members, just enough created the tipping point.

So what does this tell us about the US election process?

No matter that that population has gone from an estimated 2.5 million in the original thirteen colonies to over 320 million, each vote does count, and that vote can be influenced, even until the last minute. Although the Founding Fathers worked with a set of social issues and technical capabilities that are quite antiquated, the premise of popular vote backed by the Electoral College has proven evergreen. Through Supreme tests and unforeseen circumstances, the tremendous impact and significance of the Constitution continues the bow wave of global proportions.

Big Data Elections

So how does Big Data influence the well-established process? The first iteration is evidenced in the striking Trump victory. By creating over 4000 messages, the Trump campaign influence individuals as gleaned from their interactions with friends, family, colleagues and strangers via a suite of online platforms. The targeting itself is not a new concept; the ability to learn detail about your preferences and match them to a more specific message for you is what is evolving.

Future capability will be even more surgical. A study of your patterns will provide a unique message only you will see, not just one in four thousand. It will be oh-so-compelling and it will be timely. Pandora kept repeating the same message about Obamacare to me, which makes me question the targeting capability. It’s a subject I’m not passionate about either way so I doubt its efficacy and wonder at its origin. Future Big Data political influence will know your personal call to action, what makes you click the button in its favor.

“Big Data, Who Should I Vote For?”

As always until technologically replaced, there’s an app for that. Whereas the campaigning is the push, an app is the pull part of Big Data. Today’s voting apps provide information about the candidates, which is good, but they don’t utilize Big Data. The Big Data Voting app first understands all your personal data profile: social media, work habits, employer and pay history, geotags of your life. The app crawls the political schema to search the candidates and party habits and messages, even determining where the rubber doesn’t meet the road (do they do what they say?).

The app doesn’t tell you for whom to vote, but it does profile your activity against the candidates: what specific messages and actions truly align with who you are and what you do.

The app is even more effective at the levels below the Presidential race. The app will better sort out the voting records of constituents to let you know how their actions align with your profile proclivities. Digging down even further, it would provide a more robust picture of those local officials that this election you might not have heard of before seeing the ballot. Positions like school board members and county officials and judges have tremendous impact on the tactical level of our lives, and yet we rarely have much information on their backgrounds or voting records. (Or we don’t take the time to search the various resources for that information.) The app would do the heavy lifting to provide a decision dashboard. It’s less emotion and more metrics.

Big Data Creates the Slate

The rhyme and reason for individuals to pursue an elected position is far from a perfect process. Like even our Founding Fathers, the credentials for running for office have more to do with whom you know and how much financial capability you have than actual capability for executing the duties.

Further in the future, Big Data would start the election process by picking potential candidates out of the crowd. A Big Data candidate proposal process would cull the general populace to find individuals with demonstrated good character and decision capability.

Big Data isn’t Big Brother though. At the polls, it doesn’t vote for you. It rises above the emotion and motion of the crowd to provide a better understanding of what your habits and proclivities actually mean in political perspective.

End of Day

The prescience of the US Founding Fathers is almost unfathomable. The Founding Fathers took great care and incredible insight to vision a government that would live in perpetuity – through a magasmaum of unforeseeable technological, social and political changes.

Perhaps had they known all the challenges ahead, it would have presented an impossible undertaking. They didn’t even have electricity. Consider the cascading inventions, capabilities and perturbations from that singular effect. I’m glad they didn’t have any idea how many ways the world would change or how many times their work would be challenged; otherwise, the Founding Fathers may have just stayed home.

The morning of the 2016 election held no obvious portent to one of the most unforeseen comeback victories in the US. I made my coffee hurriedly that morning.   Although my employer had no qualms about my being late, I still had to fit voting into the day’s routine. It wasn’t a significant weather day, no hailstorms or raging battles or extremist groups to deter turnout. I had to travel a torturous (joking) four blocks to reach my voting location. The only army there was volunteers (some paid) that made the process about as efficient as possible for an ad hoc group of strangers enforcing the rules. How easy is that!

I thought of that night in Kenya again, realizing how my single vote made a difference not just in my country. As small as the planet becomes in a Big Data world, all the more so every one counts.

 

 

2018 Guide to Big Data (5 Easy Concepts you need to know today)

Big Data innovations continue to drive business intelligence and integrate into everyday life. Whether you are an experienced data scientist or an aspiring one, whether you are in big business or a one-man shop, whether you are worried about your weight or what your government is doing – Big Data is a part of everyone’s future.

Big Data made a Big Difference in the biggest story of 2016 – the US Presidential election. Although President Trump had pooh-poohed the impact of Big Data during his initial campaign, he rallied a last minute expert team just months before the polls that just may have made the difference.

Using sophisticated analytics and digital targeting, President Trump’s technology strategy collected characteristics from online and offline sources to find potential voters. With over 4,000 finely tuned messages, a specific one was placed after assessing the potential voter’s Facebook, Pandora and snapchat activity. Virtual grassroots at its finest.

Bringing Big Data to the people.  So, what is Big Data and what concepts do you need to know right now?


What is the big deal about Big Data?

Big Data is the collective term for the accumulation, processing and utilization of lots and lots (and lots) of data.  Big Data is huge quantities of data – Volume. Big Data is an array of types of data, from an equally diverse set of sources – Variety.  Big Data is collection and interpretation at ever-faster rates – Velocity. These are the “3 Vs” often referred to in discussion of Big Data.

Although humans have been collecting information about what they do and create since the beginning of recorded history arguably somewhere in the Roman Empire, Big Data is the relatively recent capability to capture and process such significantly larger and more robust data sets. Although computers began the data accumulation in the 1950s-70s, the phenomena of Big Data evolved as recently as 2001 when the term was coined by analyst Doug Laney.  What makes the BIG in Big Data is the exponential increase in the 3 Vs discussed. Here’s a couple of examples.

The Big Picture

When the Sloan Digital Sky Survey began in 2000, its telescope in New Mexico collected more information in the first few weeks than had been amassed in the entire history of astronomy.  By 2010, there was over 140 Terabytes of information. That amount of information can now be collected every 5 days.

When scientists first decoded the human genome in 2003, it took them a decade of intensive work to sequence the three billion base pairs. Now a single facility could sequence that much DNA in a day. The cost of that processing went from $40 million to $5000.

What data you can store and process on your phone today in 24 hours has probably more capability than all computer processing up through the 1970s. In 2005, a cell phone – without even a camera – had more processing power than NASA’s mission control during the Apollo flights that put men on the moon.

To understand why you need to know about Big Data, let’s start with The Fab Five.

 

 

#1 Not a Fad

In the past decade plus years, the 3 Vs of Big Data – Volume, Velocity and Variety has gotten a lot of attention from techies, industry and the public. There’s even been a fourth (Veracity) and Fifth V (Value) to further explore its opportunities and challenges.  Like any popular uprising, the hype or substance of Big Data (depending on how you look at it) reached a certain level of attention before the naysayers began to cast the first predictions of if being a passing fad.

To some, Big Data melts into a crucible of technology slugs and ingots that are pedestrian and passing. But it’s not. The volume, velocity and variety of data available today, versus last year or ten years ago are not about to peak. Following the Second Law of Thermodynamics, its disorder only increases.

https://michaelhanley.ie/elearningcurve/learning-curves-workplace-environment/

Big Data is still in the flat slope climbing the learning curve of what Big Data is and isn’t or what it can and cannot do. Utilizing its capability has considerable challenges, ranging from how it is initial collected to how to get to its mined “gold” – prediction. The philosophic trellis supporting Big Data is complexity and chaotic systems. It’s tricky stuff that the best experts are still beginning to explore.

It’s all emerging technology with all the nubile stumbling of a toddler.  As its potential is only unfolding, the impact of Big Data is less like a popular novel and more like the Gutenberg bible. The bell can’t be unrung; it is here to stay.

Business uses it. Government uses it. Non-government organizations and non-state actors – both beneficent and malevolent (terrorist) – use it. And you use it too.

 

 

#2 You’re Wearing It

Wearables continue to infiltrate everyday life. Right now, the obvious example is your mobile phone. Somewhere in 2014, the number of cell phone subscriptions rose to equal the world population. (Land lines in the US never made that ratio, peaking way back in 2000.)

Cell phones provide you with more and more capability that is also your identity. It’s not just contacts and email connectivity. It’s not just communication. It has your banking information. It has your pics and music and social media, all brimming over with the 3 Vs of data. It entertains you and provides you with convenience. Some argue it is also security. It tells you where you are as well, and as it captures everywhere you have been.

Wearables have become increasingly popular with connecting into more robust medical applications – blood content, vital signs, respiration. Shoes have been designed to give directions to the blind. Socks can charge batteries with walking. These may seem like cool or awkward technologies but their implementation will break barriers in ways that aren’t obvious to the casual technology observer.

Wearables aren’t just for humans either. Wildlife is tracked for numbers and habits. Domestic animals also wear their own version of biometric sensors. The data analysis is used to optimize breeding and feeding practices. Even a honey bee can be fitted out for tracking movement for scientific experiment. These are data points that have been available in small portions before, but as the cost has gone downward, the capacity of data to be analyzed has gone up. Before it was a few discrete points; now it is a flow with more robust and significant and actionable outcomes.

Wearables are moving into more platforms and becoming more ubiquitous. They can be literally woven into fabric and painted or embedded into the skin. The Big Data doesn’t stop capturing your life though with wearables. It keeps going.

#3 It’s All Around

Wearables are just a subset of the propagation of sensors embedded in every aspect of life. Sensors will continue to combine with increased ability to interact and utilize that information. This – the Internet of Things (IoT) – started as a cool idea, but you can bet it already has effect in your life. You are always “on”.

Mobile phones and wearables are examples already provided, but there are others you already know. A suite of home monitoring products on the market provide remote control and observation to check on your electricity usage, environmental status, fire protection, doors locked. You can add monitoring to your car as well, and new models are incorporating more and more sensors that analyze its operation, alerting the driver to hazardous operating conditions and providing maintenance observations.

The Internet of Things (IoT) monitors crop growth. It’s used to drive building space utilization and builds maintenance plans for that building. Big Data and the IoT predict the weather and provide direction for recovery efforts when weather goes awry. The IoT is tolls tags in your car that don’t impede traffic and intelligent labels in your clothing that provide wardrobe inventory analysis and suggestions.

As the Internet itself is the eruption of software – bits and bytes that have become the blood of life, the Internet of Things (IoT) is essentially the physical hardware that we touch and manipulate connecting to the data flow. The embedded technologies weaving together your daily life are becoming more robust, providing an increase in productivity, an increase in relevance, and increase in well-being.

Consumers and society want this capability and they are willing to sacrifice at least some privacy and security for the perceived benefits. See Who’s Betting On the IoT.

#4 It’s Your Business

Big business has been the early adopter of Big Data and it touches all aspects of business – product/service development, manufacturing, operations, distribution, marketing, sales. More importantly, Big Data affects the most important function of business – the bottom line. Big business has had the deep pockets to explore the emerging technology, recognizing the not only the potential return on investment but also the danger of competitive advantage. As Big Data expands, the cost of entry is decreasing as the availability of resources extends to smaller businesses and individuals.

At last year’s (2016) Paris Air Show for example, Bombardier showcased its C Series jetliner that carries Pratt & Whitney’s Geared Turbo Fan (GTF) engine, which is fitted with 5,000 sensors that generate up to 10 GB of data per second. A single twin-engine aircraft with an average 12-hr. flight-time can produce up to 844 TB of data. In comparison, at the end of 2014, it was estimated that Facebook accumulated around 600 TB of data per day; but with an orderbook of more than 7,000 GTF engines, Pratt could potentially download zeta bytes of data once all their engines are in the field. It seems therefore, that the data generated by the aerospace industry alone could soon surpass the magnitude of the consumer Internet.  

http://aviationweek.com/connected-aerospace/internet-aircraft-things-industry-set-be-transformed

We live in a world of increasing choices. The Mad Men marketing schema are iconic caricatures of what capability has begun and will continue to evolve. Your computer already learns from your search history what products and services you are at just thinking about purchasing. That’s a linear example. You search; the sites you visit take the information from your activity to pitch you products and services you are more likely to want. In a way, it’s annoying. In a way, it is convenient.

Big Data will make the message more compelling and more satisfying as it is derived from multivariate activity that accumulates from the 3 Vs. It’s going to start passing products and services you didn’t’ know you need (or want.)

“A lot of times, people don’t know what they want until you show it to them.” – Steve Jobs

Big Data marketing will know your transaction history, your lifestyle patterns and deviations, and fashion a very, very personal sales message to you (whether you like it or not).

 

#5 Your Tax Dollars at Work

Governments are getting into Big Data, not so much by leaps and bounds, but more by specific experiments. The United States uses Big Data in several agencies. Fraud, default and illegal activities can be detected or even predicted by observing the huge volumes of data available from agencies that use a huge volume of transactional data, like the Social Security Administration, the Federal Housing Authority and the Securities Exchange Commission. In the interest of public health, the Food and Drug Administration and Department of Health and Human Services utilize Big Data for better decision-making on the impact of individual lifestyle choices.

The Department of Homeland Security is another obvious player, utilizing the 3Vs of data available from not just federal sources, but state and local law enforcement entities. In the aftermath of the Boston Marathon bombing, over 480,000 images were ingested for investigation. Cross pollination of NASA and the US Forest System Big Data resources coordinated to better predict weather patterns affecting ground and space events.

The next wave of Big Data in government goes even further. It’s a bit more “out there,” and it is a little scary. China citizens have stopped using wallets and instead use their phones for all transactions.  At first it was simple and convenient for buying groceries or renting a bike, but it has evolved into personal credit and social monitoring. Big Data or Big Brother, only the Chinese government algorithms know.

 

Greater Good

The 2018 Guide to Big Data has the 5 things to know about Big Data; it’s not just big business, although that group will continue to invest for both ROI and competitive advantage. Big Data also isn’t just about lifestyle choices. Wearables and the Internet of Things are building a Big Data trellis that grows the fruit of your life. Businesses that utilize Big Data will nurture that fruit, providing the tools and subsistence to grow the optimal grape.

Big Data is also about a bigger picture too. Ill intent will continue to undermine the soil and bind the vines. The bad guys aren’t going away; they will continue to find new ways to steal, or worse.

Big Data can do really great things. It is used for disaster search and rescue as well as damage assessment. It’s used for wildlife assessment.  It brings together the people throughout the world who want to help.

Is Big Data a silver bullet or final solution? No. Big Data is only just beginning. Is all the technology in place? No. But we did see Big Data turn the tide of the US Presidential race.  What will happen in 2018??

Stay tuned.

Big Data, Bird Flocks and Figuring Out World Hunger

Do you notice the flocks of birds that pass overhead?

I love watching the graceful flow of the flying inhabitants of the beach: pelicans, sandpipers, seagulls, cranes. Some are ‘regulars’ – seen day after day. Some come and go. Last week I watched an array of over 20 stork-like creatures I’ve not seen before fly by. Another favorite is the transitory flights of geese that mark the passing of time through the change of seasons. I am a far cry from being a bird watcher though. I just enjoy observing.

Rewind a couple thousand years to the pre-republic days of Rome. Bird watching was more than a hobby. The augur or auspex was a religious official who observed natural signs, especially the behavior of birds, interpreting these as an indication of divine approval or disapproval of a proposed action. He (always men) derived the gods’ intent from how the birds flew. In this highly esteemed position, the Augur watched for bird movements in the skies at specific times for signs to regard holidays or elections. They also watched in general to portend evil activity or warn of possible enemy movement. This bird observation was reading the auspices. People would consult augurs for guidance on personal matters too – from business dealings to wedding dates. Government officials consulted the auspex for holidays. Roman military campaigns would utilize augers before battle.

Murmuration from Islands & Rivers on Vimeo.

Big decisions … based on how the crow flies (figuratively)

Seems silly or crude? What do the birds know about politics, or war plans or whether this year’s crops will be fertile?

Bird traffic does provide information though.

Romans didn’t have computers or cell phones. Romans didn’t have weather forecasters; they didn’t have any way to know what weather was coming. The best they could do was look out the window or maybe across a field. How many times has that worked out for you when trying just to predict the commute home?

Bird activity does say something about current conditions in the air, water and earth. A single bird can go further and see farther than any human many times over day after day. Their action as a group signifies a coalition of instinct and knowledge. They also fly upon air current, which is driven by barometric pressure, which is result of uneven heating of the earth’s surface, which is … weather. If today we were stripped of so many data sources taken for granted, perhaps we might learn to study the signs of nature very, very, very carefully. We would want to be able to predict bad conditions, or worse – disasters.

Not Ancient History

“First news from Galveston just received by train which could get no closer to the bay shore than 6 sq mi (16 km2) where the prairie was strewn with debris and dead bodies. About 200 corpses counted from the train. Large steamship stranded 2 sq mi (5.2 km2) inland. Nothing could be seen of Galveston. Loss of life and property undoubtedly most appalling. Weather clear and bright here with gentle southeast wind.”
— G.L. Vaughan
Manager, Western Union, Houston,
in a telegram to the Chief of the U.S. Weather Bureau on the day after the hurricane, September 9, 1900

It was the early days of fall in 1900. The deadliest hurricane in US history struck Galveston Texas with little portend. The day’s weather forecasting methods did not predict the 15 foot storm surge that covered the entire island that lay at a mere 7 feet. Entire buildings pulled off their foundations and 145 mph winds ripped at whatever held above the tide. The deaths were only able to be estimated and reached 6,000-8,000.

By comparison, Hurricane Andrew struck Miami in 1992 with all the full warning of the National Hurricane Center as the mighty Category V storm hit with winds of 165 mph. Miami’s population alone was hundreds of thousands more than turn of the century Galveston, and over 1.2 million people were evacuated from Miami and surrounding counties. The result was a still unfortunate loss of life, but minimized to 65 persons.

Even by 1935, the Weather Bureau was able to send widespread warnings and Coast Guard aircraft even transited the shoreline dropping message blocks concerning an approaching storm. The effect was apparent when the most intense storm to ever hit the US travailed upon the west coast of Florida with over 185 mph winds and 18 foot storm surge. Deaths were curtailed to an amazing 465.

Obvious, and less obvious

Weather affects everyone, every day. What to wear? Need an umbrella? How about needing disaster response? That’s the direct, tangible effect. Weather also has indirect reach: how well crops grow, the cost of those crops, the economy that depends on people affording and eating those crops, the politics that influence all of those reaches.

So without telecommunications or computers or the mechanics of electricity or the knowledge of weather, perhaps studying the birds was actually pretty damn smart. The Romans had a lot of good ideas, tangibles such as roads, bridges and aqueducts that are still in use today. Their influence too is in our government, architecture, language, law, and military tactics and equipment.

Data use has been likened to searching a dark room with a penlight. The room is stacked to the ceiling with information, but we can only find what we need within the narrow confines of a very small beam. This is a great comparison to the Romans using birds. They were right, but context and content were still in the works. They did a helluva lot with what they had.

So How Does Bird Watching relate to Big Data?

Big Data gets a lot of attention. It’s not quite the reverence given the Roman augurs, but it does tend to attract believers and non-believers.

Like the augurs, Big Data is not wholly left brain activity. It is not a Newtonian equation that takes variables and outputs a product. But as Einstein first got us bending time with thought experiments about quantum capability, the Laws of Nature aren’t as solid as we think.

If we stay within the Left Brain and Newton’s confines, we will eventually be trapped there. That’s why cancer, hunger, and terrorism are still very much a part of our world. These are Big Problems that require human interaction with data in ways we haven’t figured out yet. These challenges are dynamic and non-linear. Cause and effect thinking fails.

“Chaos theory becomes critical in understanding the way things work.  We must look for flow patterns rather than linear cause-effect explanations. ”  – Jean Houston, Forward for Chaos, Creativity and Cosmic Consciousness

Our world is chaotic, not in the conversational context of pure disorder but in the scientific posture of “behavior so unpredictable as to appear random.” Chaotic study has proven things are not random as they appear; it is only our ability to perceive the patterns that emerges. That is where Big Data begins.

Unlike the augurs

Big Data is nascent capability. The tools and techniques to master its volume, velocity and variety are as yet quite experimental. The pen light has perhaps grown to searchlight proportions, but now the room has expanded into coliseum size. The beam too is not quite a surgeon’s hand but more so likened to an elephant meandering through the jungle. Strong, powerful, with significant intelligence and excellent latent memory but … not so delicate.

So there is knowledge in bird flight patterns. So there is more knowledge in the 3 Vs of Big Data. It won’t be Newton’s apple clunk on the head; it will be in the whispers and wails of the wind and our ability to interpret the direction.

Why Can’t it be (Christmas) Tax Season All Year Round?

With the joys and boys of summer fresh upon us (in the Northern Hemisphere), it spoils the fun to bring up taxes. Summer is time off from school and most of society either joins in or gets the heck out of the way.

So why bring up taxes? There are better things to do!

Unlike Christmas, taxes ARE a year round evolution. Every paycheck or dividend return is a taxable revenue event. Every mile driven and bill paid has potentially tax significance. The smartest of us plan their taxes carefully, using each day each occasion to maximize yield against risk. Tax planning is a bit of an art. Those that can afford it pay a professional and the rest of us need to study up. Accountants aren’t tax planners either; their job is to keep you from getting audited, which is contrarian to minimizing the tithe.

Sadly for most – “the number” is a random lottery that hits on or about April 15th (in the US.)

So how can that change?  

Let Big Data be the Big Brother of tax planning.

Small Data taxes is the W-2 or 1098 or form X that arrives with the snowdrifts on your doorstep in January. If you’re good, you have a system for collecting them all neatly. If you’re great, that file started long ago with the various receipts of life. With all the other faded New Year’s resolutions, you vow to “do them early this year,” whether that means sitting down at the computer or sitting down with your accountant.

Always On

The Big Data tax file accumulates every month, every day, every minute. It’s a continuous flow of information that absorbs records and sorts your transactions as well as some actions and secretes a constant number on demand. Your tax “number” sits on your life’s dashboard along with the today’s stock report and how many steps you took.

If you want to burrow into the Big Data tax data, you can set parameters or let it roam free. Big Data taxes finds the patterns you don’t see. Big Data knows you’ve hit a limit or a new variable. Big Data even talks to you, “what if …” you beckon, and it responds with … another number. Uncle Sam meet Siri.

Intuitive

This technology isn’t available today but it is quickly rounding second (or third) to come home. The data is definitely THERE but perhaps Turbo Tax hasn’t quite tapped the line yet. Batter up and Seasons Greetings!

 

 

Many thanks to my friend at Intuit who let me bend his ear on this idea during the eMetrics conference this week in Chicago.  You know who you are 🙂