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The Connecticut FileMaker Developer’s Group will be hosting the next meeting on May 21st at 10:00 AM in the Student Center at the Central Connecticut State University. Tim Neudecker from Kyo Logic will demonstrate the synchronization tool Mirror Sync 2.0 from 360works.com We will also start our special project. Rich Austin will present his needs requirements to the group for an inventory tracking system for fire trucks. The group will discuss the possible ways FileMaker can fit into the work flow, and direct Rich in the building of the solution. ——————– Connecticut FileMaker Developer’s Group Meeting Wednesday, May 21st, 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.

The business technology landscape is constantly evolving. For organizations, it is becoming increasingly important to keep an ear to the ground and make sure they are keeping up with the times. Organizations that fail to do that could find themselves outdated and suddenly scrambling to catch-up.

One area of business that has been evolving quickly over the last few years is the database. With more solutions becoming digital, the amount of information that is suddenly available is growing. However, managing all of this data has become increasingly difficult.

A recent article from Database Trends and Applications spoke with Anne Buff, a Thought Leader for SAS Best Practices at SAS Institute. The interview was held in preparation of the upcoming Data Summit that will be held in New York from May 12 through 14. Buff will be one of the keynote speakers delivering a speech called "Oh, Shift! How Big Data Is Calling for an Enterprise Data Rethink."

Her biggest point is that data strategies are evolving and many organizations need to take some time to re-evaluate what they do.

"Big data is still in its early stages. A lot of that is because people don't quite know what they are going to do with it yet," said Buff. "They know what it is, they know where they can get it but they have not quite figured out what they are going to do with it. Right now one of the biggest things is just trying to define what big data means to an organization."

With the help of a managed IT services software provider, any company can start revamping its strategies and improve how it uses data.

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.

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. 

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. 

In this space, we've discussed how Big Data principles can help you make better hiring decisions. Now, with the right database and some shrewd analysis, it can help you determine which employees deserve to be promoted — and which ones should be shown the door. 

It's difficult, bordering on impossible, for any manager to be completely objective about his or her staff. You get to know certain people better than others. Some employees are great at appearing to put in a lot of effort without actually trying very hard, and others have a difficult time promoting the good things they are able to do. 

In a big company, with a huge staff, these sort of imbalances even themselves out over the course of time. Even if the promotion/firing process isn't as efficient as it could be, the sheer size of the business serves as some insulation against a few less-than-productive members. For a small or medium sized business, however, every employee is a vital cog in the machinery that keeps things moving forward. If one isn't working properly, it's time to make a switch. 

That's where FileMaker support can help. 

Instead of being forced to simply use the eye test and determine which employees seem to be the most capable, you can actually create a database that will identify the metrics most accurately correlated with success. The results could end up surprising you: criteria that seemed negligible may in the end wind up being big drivers of sales. In addition, a more data-driven promotion process will more accurately reward the best employees, and allow you to cut yourself free of ones that are hampering productivity. 

Attached are the zip files for the FileMaker 13 certification Exam Review. These files were used in both the CFDG and BAFDA meetings. Please feel free to study these as needed when getting ready for the FileMaker certification test. If their are any further questions please feel free to contact Tim Neudecker at tim@kyologic.com

Files: Certification Part 1_0

A strong company starts with the right employees. If the people carrying out your strategies aren't talented and capable, it won't matter how worthwhile your vision is. Thus, being able to hire well should be a priority for any business. By identifying and retaining the best possible candidates, you can put your company into a position to thrive. 

It's a process that could benefit from FileMaker help. 

Hiring is by its nature an inexact science. Not only do you need to evaluate a person's skills in a short period of time, usually on the basis of nothing more than a resume and a handful of brief interviews, you also need to envision how they fit in with your corporate culture. Somebody who is perfectly suited for the role might not fit in with the rest of the staff. If this is the case, you've wasted your time and prevented yourself from having the best possible team.

This is where analytics come in. Parsing data on your current employees, as well as on the candidates you are looking for, can help you decide what metrics are actually important for a particular job. The answers could very well be surprising. Building the right database can even give you a way to incorporate information that would otherwise be tricky to mesh. In a recent article on Wired, author Michael Morrell discussed these sorts of criteria.

"Remember that personal interaction and communication provide perhaps more important data than massive amounts of publicly available data. Did a candidate respond to an email? Show up for an interview? And of course there are the personal referrals and references, which should carry a lot of weight in a matching algorithm," writes Morrell.

In addition, a stronger adherence to big data processes in hiring will benefit job seekers. Potentially talented people who have had issues showing it will be evaluated more holistically, which can take some of the pressure off of resumes and cover letters, both inexact proxies for actual talent. If hired, they will also be much more likely to fit in well with the company, since they would have been selected for traits that make that a likelihood. 

It's a win-win: businesses get the best possible staff, and candidates find the best possible working situation. 

Residents across the Northeastern part of the United States, from Ohio to Maine, are in the process of digging out from the first major snow storm of 2014. Some areas have seen as much as two feet of the white fluff pile up and keeping the roadways clear is becoming increasingly difficult. On top of that, the below-zero temperatures are making road treatment processes less than effective.

This scene is not unusual in many parts of the United States during the winter months, but there is a new innovation that is making snow removal and road work much easier.

A recent article from the Daily Camera, a Boulder Colorado newspaper, profiled the National Center for Atmospheric Research (NCAR) and the new "smart plow" it developed and is testing in Michigan, Minnesota and Nevada. The process works by analyzing information from several databases including satellite and radar observations, computer weather models and real-time data collected from special sensors outfitted to plows that are clearing the streets.

The goal is to continuously monitor weather conditions and keep up with trouble areas more effectively. This will reduce accidents and save states potentially millions of dollars in maintenance.

"Whereas in the past, drivers would have some new data maybe every 30, 40 or 50 miles, now you could just look up every mile, and hopefully pick up the more subtle small things that happen on the roadway," said Sheldon Drobot, the NCAR scientist who has overseen the system's design.

This is just another example of how custom database software can be used to harness big data and improve an aspect of daily life.

Getting involved with large-scale analytics is an important first step. Working with a FileMaker developer to design a way to collect, sift and categorize your data can pay immediate dividends. If you want to take your analysis to the next level, though, it might be time to think about visualizing.

Simply put, "visualizing data" takes the information you have and organizes it into in image to highlight particular trends. It isn't meant to supplant spreadsheets, but rather to enhance them. This process creates an ease of communication that facilitates cooperation, and can turn a meeting from a slow process of poring over numbers, to an efficient exchange of big ideas. A trend that might not stand out when it's amid other numbers on a screen could suddenly become obvious when displayed in another format. 

You can even adjust it so that the image updates in real-time. Using color and design, these snapshots can tell a high-level story about your data, which the information itself can then elaborate on. If, for example, you are trying to sell a potential client on the efficacy of your product, a graphic representation might be more visually arresting. Once you've created that interest, you can use the particulars to support the narrative. 

This approach also pairs well with using a service like FileMaker. Since the software allows you to parse your information so quickly and efficiently, it's simple to create visualizations that can highlight a variety of different factors. Using images is yet another way to use the powerful tools afforded by Big Data to create approachable and workable takeaways.