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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.

Retail is one of the most natural possible frontiers for the implementation of Big Data. There are hundreds of individual transactions that occur every day, and the margins businesses work under are narrow enough that any advantage, regardless of its size, could be crucial. Here's how you can get the most out of using analytics:

Use every available resource.

While the data that you collect might be a good start if you're a small shop, it probably pales in comparison to the amount that's actually out there. Being able to incorporate freely available information into your proprietary custom database software can be a cheap and effective way of realizing valuable insights. 

Consider the sales you didn't make.

Too often, companies just think about their current customers, and break them down into particular categories. It can be equally important to consider the conversions that didn't happen, and examine what factors were impediments. You should also be keenly aware of your potential market, and look to demographic information that can better help you to address segments that you're not reaching properly. 

Create a context. 

The proper framework is a critical part of getting the most out of Big Data. Matt Felton of Datastory spoke about the value of this process. 

"There's plenty of patterns to be discovered in big data alone, but you miss the really good ones if you analyze this data out of context. If you're simply looking at the patterns in the data you collect, you're limited to discoveries about the things 'you know you don't know,'" he says. 

Make it manageable

The amount of data is getting ever more vast, and it's difficult to completely parse it all. Consulting with a FileMaker developer is a good way to create workflows that you can translate a lot of noise into valuable signals. Instead of trying to do everything, focus on one particular facet of the experience: try improving your customer service funnel, or your welcoming channels or your loyalty programs individually, before making a lot of wholesale changes at once. 

Look to the cloud

There are a ton of services now that will help you manage information virtually, so it's easy to access whenever you need it. This can help you make decisions in close to real time, without having to wait for tedious loading times. 

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. 

The thing about Big Data is that, well, it's big. Not only are thousands of years of information collated and stored online, there are the millions upon millions of interactions that are constantly happening every day. From online transactions to social media posts, managing the sheer amount of data is a daunting task even for the most specialized custom database software. For many companies, this volume is tantalizing, but also intimidating.

The challenge, of course, is to corral all of these disparate pieces into a format where they're usable — it's why spending on Big Data IT was somewhere in the range of $34 billion last year. Companies are interested in not only collecting the information, but also parsing it and deriving actionable takeaways. There's precious little good in having a tool if you're having trouble properly wielding it. 

That's part of why there's such a big buzz about IBM's Watson. Especially after it handily dispatched Jeopardy champions, proponents have thought of it as the next big thing in analytics. There are now 2,000 sharp minds behind it, who are bolstered by $1 billion in funding and the freedom that comes with being a standalone entity. Never before has there been such a concentrated expenditure by a single company on the implications of Big Data, so companies that are interested in using these techniques are keeping a close eye.

Ultimately, some of their findings will become part of common practice. It's this endless capacity for growth that makes the analytics industry one that  is so important to invest in. 

Retail and Big Data form a natural partnership. Companies want to be able to best serve their customers, consumers want the best possible experience, and the widespread availability of information has proven to be an efficient way to bridge that gap. It's no surprise, then, that this relationship was all the buzz at this year's National Retail Federation convention.

Hundreds of vendors gathered to show off and discuss their wares, which is good news for related industries like software and analytics. These ancillary businesses found that retailers were much more likely to spend on their services, indicating that there was a definite shift towards respect for the utility of Big Data.

Even in a slowly improving economy, many retailers are feeling the squeeze and have had to slash prices to drive sales numbers. It's no wonder that they're coming to the conclusion that a FileMaker developer could be the key to their concerns: the better they can discover and target their intended market, the more readily they will be able to convert consumers.

Ginni Rommetty, chairman and chief executive of IBM, addressed a fascinated crowd on Monday.

"This is a new era of man-machine collaboration," she said.

She went on to explain that the very same sort of technology that allowed her company's Watson computer to handily defeat Jeopardy champions could be applied to learning more about what people like to buy, and why. In fact, she went on to say that this sort of data gathering will be as germane to business as steam in the 1700s and electricity in the 1800s. 

And if the buzz around the convention floor is any indication, few, if any, of these companies want to be left out in the cold. 

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.