What is Big Data Doing in the Congo (with little cell coverage & no power)


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like a pin to a map

Attaching data to location is the basics of science and application of geospatial information and it is one of the oldest platforms of data accumulation. Since That Guy claimed ownership of That Land, there has been some documentation of specific reference points to plot out control. That system of record has increased in sophistication over the millennia. Today’s land surveys would surely have impressed George Washington, and that’s not just because it utilizes satellites and Global Positioning System (GPS). Government utilizes Geographic Information Systems like this.


Urban planning is only one of today’s many Geospatial Information applications that provide decision making capability for disease control, global participation, environmental monitoring, and wildlife management to name a few.

Big Data doesn’t have to be all high tech or even high speed though.

Even in the “dark” of the Congo, with limited mobile connection and no electricity, geospatial information is solving a cultural and economic problem.


Support Systems Limited deploys the latest ESRI GIS techniques and tools to provide effective solutions and support to a broad range of user organizations and a wide variety of industries.

Extreme Citizen Science (ECS)

Citizen science is the involvement of non-formally trained participants in science experiments. Citizen scientists, regardless of expertise, record observations or perform experiments toward a project. Considered by some as crowd-sourcing surveillance, citizen scientists date back to the “gentleman” scientist and include such notables as Sir Isaac Newton, Benjamin Franklin and Charles Darwin. Some debate exists as to the validity of the citizen scientist; however, the most beneficial application appears to be combining the talent and expertise of formal scientists with those directly enthusiastic about or engaged in the research.

With that thought, what better team than an indigenous population and the scientists that want to help preserve their culture? Anthropologist Jerome Lewis of the University College London (UCL) is part of the team of Extreme Citizen Science (ExCiteS) research group assisting the Mbendjele, a nonliterate group of native hunting and gathering people living in the Republic of the Congo. Local logging company Congolaise Industrielle des Bois, certified for its environmentally and socially sustainable forestry operations, wants to utilize land inhabited by the Mbendjele. The Mbengjele don’t believe in “owning” land, but instead believe the forest to be an extension of them. ExCiteS has developed a solution for the Mbendjele and Congolaise Industrielle to each pursue their interests.

An Mbendjele love the forest as he loves his own body.” – Lewis

So … how do you protect the trees and plants that are spiritually and medically significant to these indigenous people when they don’t claim rights to the land that holds them?

The Mbendjele have specific trees and plants that are integral to their beliefs and way of life. Instead of claiming land as protected, with the help of ECS they identify the plant life that is medically and spiritually important to them. The forestry operations work around that identification.

How is that done if the Mbendjele are illiterate?

Most Mbendjele had never seen a cell phone prior to the project. They don’t have mobile devices for communication but they have been given them to use in identifying the specific location of trees and plants important to them. They take them to locate geotag those plants. Because they don’t read, they simply click on icons of their own hand drawn pictures to the plants, which tags them with GPS.  The method is an open-source Android app called Sapelli, named after a Congolese mahogany-like tree that is a point of conflict between local communities and loggers.

How is that done if they have no power, not even solar?

The Mbendjele have no electricity and solar power is limited because of the thick jungle canopy. In order to be able to charge the phones, they needed another solution. Thanks go to Hatsuden-Nabe cooking pots from Japanese TEX New Energy Corporation. When the pots are heated over an open fire, the heat is transformed into electricity to charge cell batteries. The Sapelli app is also designed to only transfer very small packets of information in order to conserve power, as well as adapt to the limited cell coverage.


The Sapelli app and its collected data are open source. The capability is welcome to be replicated or utilized for other programs or in totally different direction. ExCiteS is also using the Sapelli app in similar context with an indigenous tribe in Brazil. The app is also used in another context in the Congo and Brazil for documenting poaching and illegal operations.

In consideration of the lack of power and connectivity, it is amazing how it can be used in seemingly any corner of the world for a breadth of mission possibilities. Those that know the land form and function the most intimately can provide the most poignant data points from their perspective. The information they collect can be used immediately as well as continue to germinate for other projects yet to be imagined or deployed. Also, those data points that are significant to those right there can be examined and understood in perspective from regional and even global perspective.

This is an important Big Data tenet. Data collection doesn’t exist for one purpose, one perspective, one dimension of space or time. Because of the ability to store and manipulate ever greater volume, velocity and variety of data, we will continue to find signal in the noise.



How Africa Tweets


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Interesting graphic on Twitter in Africa circa 2013.  Johannesburg dominates for volume, and South Africa is further bolstered by Durban and Capetown.  Although it’s not surprising English is the most popular language, the numbers are interesting.  The spread over day and night is well captured too.


How Africa Tweets


Three BIG Things BIG DATA is NOT, Nor Likely to Ever Be


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Three BIG Things Big Data Is NOT, Nor Likely to Ever Be

With all the hype surrounding Big Data, determining what capability Big Data is delivering as well as what potential it has can be a bit cloudy. Some experts exhort praise for the amazing ways in which Big Data has already liberated the people to a newer level of understanding … and invested resources accordingly.

The White House has already invested more than $200 million in big data projects.

Goodness knows I can’t last two minutes after hitting unexpected traffic before I’m clamoring for my phone to rescue me with a new route or at least a picture of how long I’ll be trapped in the gridlock. That’s quite pedestrian for the glory that is forecast by some for Big Data (including me.)

Contrarians argue that Big Data is a fad or worse, a plague of unintended consequences from whatever benevolent or malevolent quest. Google was hailed for its ability to predict flu outbreaks weeks before the Center for Disease Control. Google did this by analysis of search requests for information about flu associated terms. This “nowcast” shook up predictive analysis in 2008 with much applause, providing specific flu information weeks before the CDC … until it didn’t.  The effectiveness wore off.  In 2013 Google missed the peak flu by 140%. Condemned as false prophet, Big Data does not deliver any solutions easily.

Regardless of what camp you fall into, Big Data is not, nor likely to be three things, at least for the foreseeable future.

Of course, if you could foresee the day when you’d always have a flashlight as long as you had a phone on you, you are ahead of 99.999% of us.

#1 Not a Straight Line

Big Data is not a linear process. There’s no straight, curved, looped or contorted line between problem and BD solution. You can’t walk up to a Big Data vending machine, plunk in a couple of coins and expect a sordid chain of bumps and clicks to derive the satisfying “gedunk” sound of what item you chose falling out the bottom drawer.

Big Data is a bit more like Life – it’s complex and chaotic – with all the physics and psychology lexicon trappings. A butterfly flutters its wings on the Amazon website or the South American river and a typhoon erupts in the African ecology or Chinese economy or Australian financial markets. Even holding a potential solution with intention while framing a Big Data algorithm defeats the process and purpose.

#2 Not So Scientific?

Big Data is not the traditional scientific methodology in which many have been trained to believe. The process does not involve a null hypothesis to be proven or disproven. Big Data is about observation – patterns, trends, anomalies, outliers. It’s a journey of discovery, not of certainty. Big Data creates options, not opinions.

At the end of the day, Big Data can tell what happens, which can be used to predict what will happen. Big Data though does not explain WHY, which is the more traditional demand in man’s quest to understand the world (and get one step ahead.)

#3 No Silver Bullet

Big Data is not the silver bullet that explains the WHY of the world, nor is it a solution in and of itself.  Like business productivity movements such as Six Sigma or Total Quality Management or the Deming Method or ledger of similar potential, it has famed promises and variable application.

Similarly, the Internet isn’t the answer to all questions. As Google can testify with a million search results for any given query, more data – even Big Data – doesn’t mean a singular response. It’s more likely more questions and a suite of possible solutions.

Doing Big Data for the sake of being in with the Early Adaptors isn’t going to secure the future for anyone.   Big Data should be implemented in harmony with the circumstances and ability of today’s framework. Big Data is best incorporated holistically, and in that regard, it is likened to the various business and life productivity trends before it.

Stay Tuned

Big Data is an embryonic capability. It’s a tool. It’s a philosophy. It’s a technique. It is not the pot of gold at the end of the rainbow.

If you’re still pondering it’s effect or lack thereof, consider these four stats from Forbes:

The data volumes are exploding, more data has been created in the past two years than in the entire previous history of the human race.

Data is growing faster than ever before and by the year 2020, about 1.7 megabytes of new information will be created every second for every human being on the planet.

By then, our accumulated digital universe of data will grow from 4.4 zettabyets today to around 44 zettabytes, or 44 trillion gigabytes.

Every second we create new data. For example, we perform 40,000 search queries every second (on Google alone), which makes it 3.5 searches per day and 1.2 trillion searches per year.

(16 more cool stats from Forbes)

Big Data isn’t going away. Business operations will leverage the capability, and economies will turn in tow. Societies worldwide continue aggregating greater and greater data stores, setting soliton waves into motion that have only begun to influence global and local policy.  Learning what Big Data it is and isn’t is integral to understanding how it will alter business, governments, and societies.

The mechanics of Big Data are still very much in development. The digital collection of the volume, velocity and variety of information is far from perfection, with no single or solid methodology to anchor the veracious stream. But there is gold from Big Data – for some it’s predictive analytics and for the purists it is the simple beauty of seeing what emerges. This is still an art and not so much a science.

Better voting decisions – there’s an app for that


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My 5 Big Data Themes for 2016 includes continued experimentation of Big Data in government.  Democratic republics depend upon citizens that are educated and informed about their communities, their country and their options.  Although the US founding fathers were fairly restricted on their ability to see and gather information outside relative proximity, perhaps that wasn’t so bad.  Without the limitations of knowing everything, they were free.

That might seem contrarian to Big Data advocates, but actually Big Data is exploration into how much we don’t know as much as finding out new insight.

Check out this Fast Company article on voting on you guessed it – it’s an app.



Buying books, records, and other products based on the recommendations of people in your social circle has long been standard. Now, the online petition service Change.org wants to adopt that approach to how you vote and pick your favored political candidates.

They just launched a new mobile-friendly site, called Change Politics, that provides users with a nicely designed version of their local ballot, and also adds endorsements from friends, media figures, and advocacy groups. It also allows users to ask questions of the candidates directly, says Change.org.

Change Politics helps voters “engage directly with the candidates in the lead-up to the election, and shift influence in elections from parties and paid ads, to individuals’ trusted personal networks,” according to the group’s blog.

Call it “social voting” or whatever you want, but the idea makes sense. Many voters go into the voting booth with almost no real knowledge about the majority of candidates or policy initiatives. On many, they may recognize a familiar last name, or remember an attack ad they saw.

With all the endorsements and background information users collect at Change Politics, they can build a personal “ballot guide” that they can take with them into the voting booth on a smartphone.

More informed votes has to be a good thing—with the caveat that voters don’t just go along with what their friends or favorite media figures are doing. Hopefully voters will weigh influencers based on their arguments for voting one way or another.

Change.org founder and CEO Ben Rattray says Change Politics has a chance of reengineering politics in the way that apps, like Uber, have revolutionized other industries.

“Technology has transformed power in a number of industries like media and communications, but it hasn’t transformed politics in the same way, and that’s both a tragedy and an opportunity,” Rattray told Fast Company. Really disruptive companies haven’t merely provided websites for old-guard companies in a space; he says, they’ve built apps that put the power in the hands of the individual customer.

That’s what the new mobile site will do. It’ll also improve the overall experience of voting.

“If you were a company that sold the public the experience of voting you would have gone out of business long ago,” Rattray says. The smartphone, Rattray says, is the most powerful and transformative invention of the past 100 years, and the Change Politics site will leverage it to empower voters and reinvent the political process.

Rattray points out that the main use of information in technology by political campaigns so far has been to target advertisements at narrowly defined voter segments, not to help voters make reasoned decisions.

He points out that a voter empowered with better information might make smarter choices. The democratic process itself could work better.

“The only reason money matters in politics is because you have low-information voters,” he says. And those voters are more likely to respond to attack ads they see or hear.

“If people’s attention is increasing drawn to the people and organizations they most trust then it’s that trust that becomes more valuable than money in politics,” Rattray concludes.

Other political sites have attempted to reinvent voting and have had limited success. But Change.org may be different. Rattray says 35 million people have already used the main Change.org petition site. That’s enough people to catch the eye of any national political candidate.

In fact the campaigns of many of the 2016 presidential election candidates have already signed on to interact with voters at the new Change Politics site. These include Chris Christie, Mike Huckabee, Ben Carson, John Kasich, Carly Fiorina, and Jeb Bush on the GOP side, and all three candidates in the Democratic primary—Hillary Clinton, Bernie Sanders, and Martin O’Malley.

The Fantastic and the Functional: Two Perspectives on IoT


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The Internet of Things (IoT) is different things to different people.  To someone a bit more … inspired … it is a fantastic stellar journey into the possible.  For others, IoT is a bit more functional.  Madhu Murgia reports on A few viewpoints of where IoT is going.

Marc Andreessen: ‘In 20 years, every physical item will have a chip implanted in it’

Supply chain
A new wave of Internet of Things startups are aimed at industrial uses

Madhu Murgia By Madhumita Murgia

23 Dec 2015

The hype around the Internet of Things has been rising steadily over the past five years. In tech analyst Gartner’s Hype Cycle for Emerging Technologies report in 2015, the IoT is at the peak of “inflated expectations”, particularly for areas like the smart home, which involve controlling your lights, thermostat or TV using your mobile phone.
But the era of sensors has only just dawned, according to renowned technology investor and internet pioneer Marc Andreessen. In 10 years, he predicts mobile phones themselves could disappear.
“The idea that we have a single piece of glowing display is too limiting. By then, every table, every wall, every surface will have a screen or can project,” he told the Telegraph. “Hypothetically you walk upto a wall, sit at a table and [talk to] an earpiece or eyeglasses to make a call. The term is ambient or ubiquitous computing.”
The end state is obvious – every light, every doorknob will be connected to the internet.
Which is why he has invested $25m into Californian startup Samsara, which is the first of a new generation of “internet of things” devices that solves huge industrial problems, rather than turning your fridge or your toothbrush into a portal to the web.
“This second wave of companies, they don’t want to just do “internet of things”,” Andreessen said. “They are showing up three years later, saying ok I know exactly how this is going to get used. It’s for real businesses in industrial environments.”
Gartner backs this claim – it predicts that businesses alone will double spending on internet of things units by 2020, going from $767 billion to more than $1.4 trillion.


Other startups in the space include San Francisco-based Helium, which has raised $16m from investors like Khosla Ventures and Ayla which has raised more than $25m from the likes of Cisco. In fact, according to analyst CB Insights which tracks investments, IoT startups have garnered $7.4 billion investment dollars cumulatively, having more than doubled their funding in five years.
Samsara, for instance, provides sensors and data analytics in the cloud for heavily instrumented industries like pharmaceuticals, transport, power and water.
Pharmaceutical companies transporting drugs or vaccines need to constantly monitor temperature; logistics or delivery companies track their fleet of vehicles over long distances; and perishable food companies need to monitor internal temperature and humidity of trucks to check if their goods are spoiling.



Samsara is already trialling its product with a range of industries, including well-known American yoghurt manufacturer Chobani, two multinational pharmaceuticals, and city water districts that want to monitor energy consumption patterns of water pumps, amongst others.
“The problem is that manual measurements are very common in hospitals, pharmaceutical delivery chains, and even the distribution of dairy and meat produce. Someone actually goes to the warehouse to fill out a report with pen and paper every 3 hours,” says Samsara’s CEO Sanjit Biswas, whose previous network technology startup Meraki sold to Cisco for over $2 billion.
His big idea: installing cheap sensors, and uploading and analysing data to the cloud makes Samara 1/10th of the cost of existing industrial sensors (complex systems made by huge incumbents like Intel), and deployable in under 10 minutes.
“If you want a tailored system, someone like IBM will build you a custom solution but it usually costs $5m so it doesn’t make sense unless you’re a large company,” he explains.
Andreessen is a fierce believer in the impact of this wave of software-driven sensor startups. His core thesis is that over the next 20 years every physical item will have a chip implanted in it. “The end state is fairly obvious – every light, every doorknob will be connected to the internet. Just like with the web itself, there will be thousands of of use cases – energy efficiency, food safety, major problems that aren’t as obvious as smartwatches and wearables,” he says.
A report from Accenture this year estimated that this new Industrial Internet of Things — which has also been called the fourth industrial revolution or Industry 4.0 — could boost the British economy alone by $531bn (£352bn) by 2030.

Customer Journey Analytics and Data Science

Excellent analysis of the customer experience.

Business Analytics 3.0

  • DigitalJourneys-WhyWhere do customers abandon the shopping process? Is it the same in every geography?
  • Audience of One…. Who are your fans versus haters in the marketplace?
  • How do customers feel about your products? How engaged are customers with your brand versus your competitors’ brands across social media and web channels?

Fortune 500 companies are making large investments around Programmatic Marketing, Sales and Service (“marketing that learns”).

One of most often implemented use case in Programmatic Marketing is customer journey mapping and analytics.

Why? Because, deciphering the nuts-and-bolts” of individual customer journeys online (and deducing intent) is core to improving customer experience and driving brand loyalty.

Specifically, the objectives are:

  • Visualize and map the end-to-end customer journey by personas
  • Optimizing on the right journey attributes to increase yields  by >30% lift… Uncover the right combination of web, mobile and physical channels, content and experiences that  best achieves the target goals
  • Enable marketers to identify journey bottlenecks for…

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Wants and Needs – The Heart of the Matter Still Matters

This post again is not so much about Big Data as about remembering the basics.

There’s an excellent lesson in this most excellent inspiration of serving the homeless.  The first order effect was solving an immediate need – creating a coat that becomes a sleeping bag.  The innovation is creative, relatively easy to implement and provides an immediate solution for a need.

The second order effect though was further derived from the homeless again.  To teach to fish instead of give a fish, they (the homeless) wanted the jobs to make those coats.

Always learn from the customer, those you serve.

A Tale of Two Cities – Actually the Same City – Mogadishu



Somalia doesn’t seem the likely forum for Big Data, but this Ted Talk about entrepreneurship in Somalia is more than the usual inspiration we’ve come to expect from the venue.

Great ideas and inspiration aren’t just a cool story.  Making a difference in the corners of the world comes back to everyone.

Connectivity isn’t just a cloud.  It is reaching people for physical needs, not virtual intellect.  It means opportunity for a rising tide to life all boats.

More to follow but this is introduction for a more complex concept.

5 Big DataThemes for 2016 You Need to Know


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5 Themes you need to know about Big Data for 2016

Bringing Big Data to the people. 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. What can you expect for the upcoming year? Here are 5 (plus) Big Data movements to expect in 2016.

#1 Not a Fad

The 3 Vs (Volume, Velocity and Variety) of Big Data were coined by META Group (now Gartner) analyst Doug Laney in 2001. In the ensuing 15 years, it has gotten a lot of attention from techies, industry and the public. Like any popular uprising, the hype or substance (depending on how you look at it) reached a certain level of attention before the naysayers ‘predictions of passing fads. To some, Big Data melts into a plethora of technology impacts 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 is not about to peak. It follows the Second Law of Thermodynamics; entropy – disorder – only increases.

It is still quite early climbing the learning curve as to what Big Data is and isn’t or what it can and cannot do.  Utilizing its capability has considerable challenges ranging from its initial collection to its eventual “gold” – prediction. The philosophic trellis supporting Big Data is complexity and chaotic systems.  It’s tricky stuff that the best experts are still exploring.  It’s all emerging technology with all the nubile stumbling associated with learning to walk.   It is potential that is only unfolding. The impact of Big Data though is less like a popular novel and more like the Gutenberg bible. The bell can’t be unrung; it is here to stay.

If whatever is placed on the Internet can never been truly erased, the exponential growth of data available will never regress. It can’t be put back in the box. Business uses it. Government uses it. Non-government organizations and non-state actors – both beneficent and terrorist – use it. Throughout history information in any form has always been leverage. Big Data is a force multiplier with a cost of entry decreasing daily. Ten year old cell phone technology – pre smart phone – has more memory than the Apollo lunar missions. Twitter data alone is utilized by individuals and major corporations alike to extract specific data points and observe trends. Big Data is more accessible than ever. Those that don’t understand its power will not keep pace.

#2 You’re Wearing It

Wearables will 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 peaked 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 it does so as it captures everywhere you have been.

Shouting is the likely the next-most widespread communications technique.

The continent of Africa has dismal fixed-line penetration of 1.4 subscriptions per 100 people, but 63.5 cell subscriptions.

Mobile phones though are just the obvious tree in a well-darkened Big Data forest. Another popular example of wearables is fitness bands. At first they flowed simple data points such as heart rate, steps walked/climbed, and resting into streams of information. Now they expand with more capability to track more sophisticated workouts and more in depth health recordings. These fitness band apps and mobile phone technology have morphed into watches, but that griffin has yet to really make sense, not that it won’t.


Wearables have more relevance 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 isn’t just for humans either. Wildlife are tracked for their numbers and habits. Domestic animals also wear their own version 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 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 one platform for the propagation of sensors embedded in every aspect of life.  Sensors will continue to combine with increased ability to interact and utllize that information. 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, but newer models are incorporating more and more sensors that analyze its operation, alerting the driver to hazardous operating conditions and providing maintenance observations.

M2M describes the continuous integration of the IoT as three waves.


Three phases of IoT integration

The first wave is more or less simple connectivity – the ability to do “cool” stuff with nice-to-have effects on lifestyle, like traffic information. As more and more sensors deploy, consumers take advantage of the convenience and efficiency, as well as security options. At the same time, industry and business are increasing sensors, the feedback loop spins faster. Products and services are more economically feasible for manufacturing and distribution as well as desirable to the consumer.

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.

#4 It’s Your Business

Big business has been the early adaptor of Big Data. Big Data 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 had the deep pockets to explore the emerging technology, recognizing the not only the potential return on investment but also the danger of not staying ahead of the competition. As Big Data expands, the cost of entry is decreasing as the availability of resources extends to smaller businesses and individuals.

Sensors on a single commercial aircraft generate 20 terabytes of data an hour.

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 least 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. 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 Dollars at Work

Governments are getting into Big Data, not 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: 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 the most obvious player, utilizing the 3Vs of data available from not just federal, but state and local law enforcement entities. In the aftermath of the Boston Marathon bombing, over 480,000 images were ingested for investigation. Along the same public safety thinking, NASA and the US Forest System coordinate Big Data in order to better predict weather patterns effecting ground and space events.

Twitter and social media are the latest communicate channel for politics. This pillar of public relations can more effectively spread the desired message through photos, videos, propaganda, calendar, events. Awareness and information about issues and events are readily available and social media also provides real time feedback on decisions and actions. You can “talk” to your representation and so polling is possible in the same format.  Big Data however will use analysis of social media to provide a more robust picture of substance and sentiment. Elected officials and candidates can also crowdsource suggestions for improvement or corrective measures.

The next wave of Big Data in government goes even further. But that’s not going to happen in 2016. It’s a bit more “out there,” and it is a little scary. (It’s also a topic for another upcoming post.)

Greater Good

The 5 things to look for in Big Data for 2016 cut across several aspects of our lives; it’s not just big business, although that group will continue to invest for both ROI and in order to stay ahead. 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 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 by the end of 2016 we are sure to see many new applications and success stories for Big Data – stay tuned.


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