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The Connecticut FileMaker Developer’s Group will be hosting the next meeting on March 12th at 10:00 AM in the Student Center at the Central Connecticut State University. We will have a round table show and tell about our favorite new things in FileMaker 13. Bring samples of how you have used the new features and see your peers samples. ——————– Connecticut FileMaker Developer’s Group Meeting Wednesday, March 12th, 2014 10:00 AM – 12:00 PM Student Center Central Connecticut State University New Britain, CT 06053 View the e-mail meeting notice. Subscribe to the mailing list.

Few organizations deal with bigger questions than NASA. While many companies have to deal with concerns about people thousands of miles apart, the distances that NASA is worried about stretch into the light-years. 

It's no surprise, then, that they would turn to Big Data. Custom web application development is a powerful tool, and for issues of the scope that they're dealing with, perhaps the only appropriate one. 

Round the clock, NASA has over 100 devices scattered throughout our solar system (including some here on Earth!), gathering information. They take in a lot of data — so much so, in fact, that at the Jet Propulsion Lab, parsing it, storing it and analyzing it is a full-time job. 

Because it gets so much data, sorting through it all can be a chore. The ultimate question scientists have to ask themselves is "what's signal, and needs to be kept, and what's just noise and can be readily discarded?"

To answer these questions, NASA turns to the use of complex algorithms. These computational shortcuts allow scientists not to have to observe every batch of data by hand, a task that would be literally impossible in the volumes that they're collecting. Instead, once the unmanned rovers, satellites and telescopes transmit their information to the servers, the process of scanning it and sorting it is automated. 

Kiri Wagstaff, who works in the machine learning sector of the propulsion lab, described the process that her division goes through when collecting knowledge. 

"Our software picks it up and makes a decision whether something interesting happened in the past five milliseconds. Our detection algorithm looks for correlations amongst all of the radio telescopes. If [an object is] popping up on all of them and not just one, they come together to make a quick decision whether or not to send it into classification," she told Forbes.

She's even more optimistic for the future of these devices. Wagstaff revealed to Forbes that there was room for improvements in the algorithms, especially in the area of better categorizing false events. As the algorithms get better, they will "learn" how not to prioritize these events. In addition, they will be able to move through this entire process significantly more quickly. 

For most organizations, the sky is the limit with what they can do with Big Data. For NASA, the possibilities stretch far beyond. 

For marketers, being able to use Big Data has long been a valuable skill. Understanding how to segment and describe different sectors of your customer base is the first step in providing them with a customized experience, and it takes a keen awareness of numbers to compete in today's digital marketplace. In fact, research firm Circle Research estimates that more than 80 percent of marketing professionals have turned to analytics in some way.  

Now, those same skills are becoming more and more valuable for executives. 

Big Data is no longer just about how to reach consumers most effectively. Now, it's also suffused throughout every aspect of running a business. In the past, learning how to use FileMaker might have been the domain of a single middle-manager. These days, however, these sorts of skills are becoming more germane to what it means to be a CEO. 

In an interview with Marketing Magazine UK, Drew Nicholson, the chief executive of dnx, describes the importance of these capabilities for top-level executives. 

"CMO's have been given the biggest opportunity they've had in 50 years. Data will give them insights and opportunities that they've never had before, but they have to do it well or they won't gain stature. If they use the wrong data then they'll lose credibility," said Nicholson.

Trying to decide the best person to lead your company? These days, the right candidate will need some facility with programs like FileMaker. If your organization is lacking in these sorts of skills, it's in danger of falling behind the curve. 

Much of the conversation surrounding Big Data is about, well, how big it is. The sheer volume of information available is a frequent topic of discussion, and for good reason: an absolutely startling amount of knowledge has been collected, quantities that were once unthinkable. While reasonable, this sort of analysis misses one of the primary benefits of the data revolution. 

Namely, that it's not just about how much information is out there but how much we can do with it. Through use of algorithms — rules that govern computational methodology — researchers can now solve complex problems with just a fraction of the time and energy. 

Consider, for example, Weatherhead University professor Gary King. One of his peers had a mass of information that seemed daunting. He estimated that it would take a highly specialized computer to get through it all, one that could cost up to $2 million. 

Within two hours, King and a group of graduate students came up with a solution. Using nothing more than an algorithm and a laptop, they figured out a way to perform the same task in just 20 minutes. 

"There is a movement of quantification rumbling across fields in academia and science, industry and government and nonprofits," explains King.

While it is undoubtedly exciting how much information can fit into custom database software, the real value in working with a FileMaker developer comes in parsing and analyzing it. Without the right structure in place, having a pile of data can be more confusing than enlightening. With the right support system, however, Big Data can open up the capability for truly stunning feats of insight. 

When it comes to Big Data, many businesses are at something of a crossroads. They have the analytical capabilities afforded by the FileMaker service, but also have decision-making processes in place still heavily tied to instincts. In many organizations, managers are unwilling to forgo their gut feelings in favor of a conclusion suggested by a database, and in such instances wholesale changes are rare. 

One of the major hurdles is that some of the conclusions suggested by FileMaker entail dealing with the unknown. Executives can be reluctant to fully embrace this concept, because they don't often have a personal history to fall back on that suggests that it will work. Thus, they consider it briefly, but ultimately default to processes they've already seen before. 

There's ample evidence to suggest that this is the wrong approach. The key to business success is flexibility and adaptation, and a company that isn't able to move forward with the times runs the risk of being left behind. Speaking to Zdnet.com, Guy Cuthbert, managing director at the visual analytics firm Atheon Analytics, described the potential inherent in programs like FileMaker. 

"I see a huge number of opinion-operated businesses that don't get why decisions could be made on data. I've listened to executives spout all sorts of opinions with no fabric or no substance behind them at all," Cuthbert said. "So if data animators and data scientists can do anything, it's to try and teach the rest of our peers in businesses that there are a fascinating number of facts located in their organization if they just choose to look at them."

Of course, this information is only relevant if it's properly oriented within the greater context of the business's mission and organizational goals: that's where an experienced manager comes in. 

The role of an executive shouldn't be to impede progress or to ignore the developments in technology that could help move his or her company into an industry leadership role. Instead, it's critical that a manager uses the instincts honed by a historical tie with the company to help contextualize new decisions within a greater framework. In that way, Big Data and gut feelings aren't mutually exclusive but rather eminently compatible. When used to support each other, they can help guide a savvy company to sustainable success. 

In a metaphorical sense, the Internet is everywhere. People around the globe share access to the same information, and can communicate with a speed and frequency previously unthinkable. 

However, the Internet is also everywhere in a much more literal sense. With the rise of mobile devices, more consumers have access to to the web from virtually anywhere. In fact, this spread is the catalyst for unprecedented growth in the amount of data that can be shared: estimates indicate that the size of the Internet will double within the next few years. 

This is big news for businesses that are able to take advantage of these changes. Mobile SEO is critical for drawing and retaining customers, and companies that don't keep these lessons in mind are in danger of falling behind: 84 percent of shoppers use their phones while in a physical retail location. 

Managed IT services software will play a big role in a company's ability to seamlessly integrate these lessons. In an article for Silicon Angle, author Ryan Cox highlights the need for this sort of development. 

"Big Data tactics + the drag-net that is required to capture that mobile data is the future of both commerce and communication. And despite being late to the party, search was invited. Mobile SEO is going to become the gateway to being discovered by the '80 percent' customer base of the future. With every passing day mobile SEO is becoming increasingly important to your bottom line, whether you realize it or not," Cox writes. 

If you're not considering how to use Big Data to engage customers, they could be gone before you realize it. 

Like Kant in the 18th century, Big Data could shift the entire framework of how we discuss and solve problems. 

Kant's primary contention was that there were two forms of understanding: analytic and synthetic. The former comprises facts that are axiomatic and based on nothing more than logic. Two and two will always sum four, even when you have no other evidence. Synthetic truths, however, are only realizable through access to external data, and can't simply be "figured out" logically. 

Until recently, computers were very good at the first sort of calculation. Given enough time and memory, they could solve incredibly complex problems, as long as the parameters were entered correctly and each step logically followed the next. 

It's the rise of custom database software that has begun to allow computers to excel at synthetic analysis. By creating the infrastructure for machines to collect and analyze data, we've garnered an ability to harness their power and apply it to the sort of complex problem solving once the exclusive domain of humans. 

Writing for VentureBeat, Venture Capitalist Zavain Dar explored this new possibility. 

"Fundamentally, we're seeing a shift in how we approach problems. By removing ourselves from the intellectual and perhaps philosophical burden of positing structures and axioms, we no longer rely on step function driven analytical insights. Rather, we're seeing widespread infrastructural adoption to accelerate the adoption of synthetic problem solving," Dar explained. 

If your business isn't at least considering a custom web application to help with its problem solving, it could be at a serious disadvantage. 

One of the most fundamental facets of police work is information collection. After a crime is committed, an officer usually has a very limited window to gather as much knowledge as possible to build a compelling case and arrest those responsible. To do so, they have to rely on every tool at their disposal, as well as their own intuition and experience. 

More and more, analytics are becoming a valuable part of that skillset. Not only can custom database software help catch crooks, it could even prevent crime before it occurs. 

There are several ways that Big Data can help in law enforcement efforts. For one, it can help departments figure out where best to deploy officers through sophisticated analysis of crime patterns. It can also help find information more much more quickly, an important benefit when collaboration is necessary. In addition, analytics can help precincts figure out how best to deploy their money and time, which can lead to big savings that can be allocated elsewhere or passed on to the taxpayers. 

Most importantly, it works. Once the LAPD installed PredPol analytics software, property crime rates dropped 12 percent in half a year. Memphis used a similar system and found a 30 percent decrease in serious crime between 2006 and 2010. 

An article in Information Week highlights the value of these sorts of initiatives. 

"Analytics above all is part of a new wave of disruptive technologies that help law enforcement agencies combat crime. It has the power to give even modest-sized operations real-time intelligence about their communities, helping better equip police officers in the field. And it promises to help law enforcement leaders develop more effective police services for the future," explains author Wai-Ming Yu. 

For any forward-thinking government agency, analytics has to be a consideration. 

If you're a retailer, it's important to know what your customers are saying about your product. You should be soliciting direct feedback from them when they actually make purchases, but it's also critical to keep in mind what they say to each other. A lot of those consumer-to-consumer conversations happen via social media platforms, a reality that many companies haven't properly adapted their Big Data strategies to. 

A social discovery company called 8thBridge investigated these findings in a survey of over 800 retailers. The businesses were judged based on their usage of seven different social platforms, namely : Facebook, YouTube, Instagram, Pinterest, Twitter, Google+ and Vine. For evaluating how well the companies questioned were leveraging social media, 8thBridge looked at traffic, brand awareness and social lift to get a picture of just how much customers were taking to the web to engage the brand. 

What researchers found was the companies were still failing to collect enough social information to make a move to Big Data plausible. While most companies have a Facebook presence, virtually none are deriving any real traffic from Instagram and Twitter: under 10 percent saw a spike in visits from the latter, and barely 6 percent saw a bump from the former. This suggests that there is a large gap between the potential of social media engagement and the reality. 

For an enterprising company, this information represents an opportunity. Oversights by your competitors in adoption of Big Data mean that working with FileMaker developers could have an even more profound effect on your ability to convert sales. There is a strong inherent value of being first in your field, so adopting these principles early could mean big profits. 

A Connecticut FileMaker developer won't just provide your company with answers to business-related problems. It could also raise some fascinating questions. 

Consider, for example, the outcome of an argument between Stanford biologist Paul Ehrlich and economist Julian Simon. In 1968, Ehrlich, an entomologist by trade who had spent time studying the population density of butterflies, wrote a book called "The Population Bomb." In it, he surmised that, at the rate the Earth was being filled up, humans were headed for a collapse. The environmental movement wholeheartedly embraced his research and used it as a tentpole for their platform. 

Simon, on the other hand, was difficult to convince. He thought that humanity was imminently adaptable, and that we would endure collapse by finding new resources or changing the ways we used the ones we currently have. He offered to back up his rhetoric with a commodities bet: in 1980 they agreed to wager on what the market price for five different metals would be in a decade's time. If the price jumped wildly, it would signal that resources were strained. If not, it would mean that society had successfully navigated population growth. 

Simon won the bet easily. Not only did the price not soar, it actually decreased significantly. 

And yet, Ehrlich remains convinced that his hypothesis was correct, regarding the need for environmental awareness. What was supposed to be an empirically provable fact turned out to lead to further contention, not less. Speaking to Planet Money, Ehrlich doubled down on his original stance, despite the fact that Simon had been proved right in one specific case.

"[Simon] knew absolutely nothing about anything important," he said. "[The bet has] become what's technically known in science as a pain in the [rear]."

There are two valuable lessons in here for managers looking to turn to Big Data. One, that the parameters that you set before you gather data are important.  While both men thought that their commodities bet would be the best way to solve their dispute, that optimism later turned out to be incorrect. 

Secondly, Big Data isn't something you can simply plug in and forget about. Your business should be constantly adapting and altering its strategies, to continue to get the most out of its analytical initiatives. It turns out, a lot can change in a decade.