Category: Uncategorized

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. 

Add some more room in the Executive Suite: Big Data experts are moving in. 

According to analyst Gartner, 17 percent of companies will have hired a Chief Data Officer (CDO) by years end, an acknowledgement of the growing importance that information analytics have in business. While in the past, these responsibilities could have been handled by a Chief Information Officer (CIO), the proliferation of Big Data has made managing it an important full-time job. 

Gartner senior analyst Debra Logan explained this necessity. 

"The CIO role is overloaded with expectations and responsibilities," said Logan. "CIOs are expected to have hands-on experience in technology, leading change management programs and project management."

Thus, to offset some of that burden and help CIOs manage their other goals, this new position has been rising in popularity. The role of the Chief Data Officer is more than just teaching your employees how to use FileMaker. Rather, the position helps organize and guide your company's analytical and information-based efforts. While having access to vast amounts of data is a potentially powerful tool, it's equally important to use it in a productive and judicious manner. 

It's important that the information doesn't end with the CDO. Instead, this role can be a valuable connector of different departments, and should become a useful liaison between the piles of numbers you're able to collect, and the financial officers who have to make sense of it all. This person could potentially serve as an advisor and an analyst, somebody who can make sense of what could otherwise be misleading data. 

Big Data has some powerful potential benefits, but in order to fully take advantage of them, managers must understand their implications. The proliferation of such a vast amount of information has changed the very currency of business: now, knowledge plays a huge role in how effective companies can be. 

And that knowledge doesn't always have to come from expertise anymore. Tasks which used to take a skilled technician to complete can now be almost entirely automated. Let's say, for example, that you manage a fleet of vehicles. In the not-so-distant past, you'd have to have a mechanic readily available for regular maintenance visits. Now, however, there are hundreds of data points that can be automatically collected and sent to you, thus cutting down significantly on the need for an expert consultation. 

Instead, the role of the technician comes in how the systems are designed and analyzed. While FileMaker development can help you identify what's wrong with your cars, it can't actually get its hands under the hood. It also needs to be "told" which parameters to look out for, something that comes from personal input. Thus, human and technological capital have to work in tandem. 

This capability also means that data, and the access to it, is a form of currency all its own. Consider the case of Google, which has built a billion dollar company based on its ability to both connect users with the information that they seek and gather data from those same consumers. If your business isn't considering the financial implications of knowing considerably more about potential customers, you're doing yourself a serious disservice. 

At the same time, privacy and security concerns have to be at the forefront of all the decisions you make. It's important to let people know exactly what sorts of information you're collecting about them, and for what intended purpose. Then, once you have it, it's critical to take steps to ensure that none of that data gets leaked. If people suspect that their personal information is vulnerable when given to you, your brand could suffer irreparable damage. 

Like anything else, you will get out of Big Data only what you put into it. If you're willing to invest heavily and learn more about how it can help you, the benefits could potentially be massive. 

Innovation in the mobile industry, coupled with the ever-emerging “Internet of Things,” has significantly enhanced the data collection process. Today, there are far more channels than ever before that can be used to obtain and hold information. But, does this make data management any better? One study says no.

According to a new report from Experian Data Quality, the number of channels we use to collect data can actually hinder management processes, resulting in poor and inaccurate information. Businesses that fail to take a centralized approach to data processing are more prone to human error. According to the study, 67 percent of organizations are missing this component of their data management processes.

“The increasing sheer volume of data means that more companies are looking to make better-informed decisions based on the information they hold,” Thomas Schutz, senior vice president, general manager of Experian Data Quality, said in a statement. “Data quality is the foundation for any data-driven effort, but the quality of information globally is poor. Organizations need to centralize their approach to data management to ensure information can be accurately collected and effectively utilized in today’s cross-channel environment.”

Ultimately, companies that pull in information from all different directions and don’t centralize their management of it may not have the ability to identify errors and make necessary adjustments to improve the quality of their data. This is where having a custom database software system in place can provide an enormous benefit to your organization. FileMaker development can be used to create a centralized system for examining and organizing information, which allows you to separate the good from the bad and improve the overall quality of your data.

Google is flush with data. It collects millions of interactions each day, from people trying to find the best healthcare insurance to those just looking for a decent bite to eat. It stands to reason, then, that the company would use some of those capabilities to help its own internal processes. 

Among the most important of those is hiring. Having the right employees is a critical part of effectively realizing your goals, and that starts with the candidate identification process. In Google's case, analytics helped the company identify that the most valuable candidates don't always come from traditional recruitment channels.

Once they were in the interviewing stage, Big Data still proved helpful. One of the major takeaways from their research was that rather than asking a series of random hypothetical questions, it was more important to figure out the behavioral trends of the person being considered. Curating questions that got to the real core of how a person is likely to adjust to a scenario was a much more valuable selection tool than simply asking, "what is your biggest weakness?"

Finally, Big Data helped in the actual hiring. In a company of that size, it can be very difficult to maintain a strongly unified company culture. By ceding some of the guesswork involved to analytics, Google is able to better pick out who will fit in. 

The same principles could very well apply to a company smaller than Google. FileMaker support could revolutionize the way you make hires, and help to mold a staff that fits well into the culture of your company and does reliably excellent work. 

When it comes to Big Data, the only real constant is change. The field is always evolving in new and interesting ways, as businesses try to figure out how best they can leverage the massive amount of information currently available to them. Indeed, one of the primary concerns of Filemaker consultants is staying abreast of new best practices and how to deploy them. 

Hadoop's release of the second version of its powerful analytics tool is the sort of update that could very well alter the way businesses approach Big Data. The 2.0 version, which became available in October, supplements cloud-based information storage with the sort of on-premise collection that could lead to further discovery in the future. This new version also frees the software from the need to process in batches, and allows it to work almost in real-time. 

One of the reasons that Hadoop 2.0 is so potentially exciting is that it dovetails neatly with the logic behind the Big Data stack. In addition to the initial technology, developers will be able to build out from it to make even more powerful software. Merv Adrian, an analyst with Garnter, Inc., described the potential of this process. 

"As people gain experience, we expect them to build larger projects," Adrian said during a recent webinar. 

This newest Hadoop iteration isn't without its flaws. The security protocols aren't yet perfect, especially because the data is being populated from public bases. This potential for risk is part of why privacy is already a big concern this year, and looks to be of high interest for the company's foreseeable future. 

The phrases "accidents happen" and "nobody's perfect" have been staples of our lexicon for quite some time, and they apply in a number of scenarios, including at work. Ultimately, businesses will make mistakes, and no organization is immune to the chance accident, regardless of its stature in its respective industry.

The companies that are most successful in 2014 aren't the ones that never make a mistake because, quite frankly, those types of organizations don't exist. The truly successful businesses are able to overcome their errors. Today, recovery can be facilitated by having the right data at your disposal.

Custom database software can give companies an edge because of their ability to identify errors in their data, which allows users to adjust accordingly. Without the hard information needed to definitively pinpoint when, where and how a mistake took place, companies will not be as successful overcoming any obstacles spurred by their mistakes. It's likely that the error was made unknowingly, so if it isn't identified quickly, it could linger, thus resulting in more series consequences down the road. 

With the right FileMaker support, your organization can create a database solution designed to capture your information and allow you to glean pertinent insights into its value. If any mistakes are identified, such as a discrepancy in your inventory numbers, you can mitigate the problem before it proliferates. FileMaker developers possess the ability to create and deliver applications that meet all of your big data needs, including the attenuation of mistakes at your company.