Without a centralized approach you run the risk of poor quality

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.

Is small thinking hurting your big data strategy?

Big data has become so prominent in the corporate lexicon that some individuals may mistakenly think they have a firm handle on the concept, when in fact their understanding is far short of where it needs to be. Even worse, many business managers are thinking about big data the wrong way, which can significantly limit the effectiveness of their data management strategies. 

An article in GigaOM suggests these people are thinking small about big data, asking questions that don't allow them to capitalize on the value of their information. According to the piece, questions like "how do we store all of this data" and "what's a different way to analyze this" represent the kind of thinking that hinders an organization's big data progress.

"This is small thinking. And it's dangerous," the article says. "Focusing on the technology and new forms of data in isolated and abstract ways will ultimately limit the value. Instead, organizations should be searching for ways to incorporate big data and data science into their existing capabilities. Preexisting business intelligence activities still have value but can be enhanced by adding new big data capabilities."

The key is to find ways to incorporate big data into your current operations and utilize it to your advantage. This might require the development of systems designed to facilitate big data management. FileMaker developers who can conduct custom Web application development have the ability to deliver systems to collect, manage and store information, all in a virtual environment, which allow you to capitalize on your information growth.

Big Data helps support vaccination policies

In many public debates, there's a certain fallacy of balance. Two sides are presented as though they're equally valid, and the answer is presumed to lie somewhere in the middle. Television, especially, exacerbates this notion: when you give both sides of an argument equal time and platform, regardless of their factual basis, it presents them as equally legitimate. 

Such is the current problem with the vaccination debate. Thanks to a few high-profile naysayers, the notion that inoculation is bad for children has gained a firm toehold in our national discussion. Even some notable celebrities have gone on record stressing the link between vaccines and the incidence of autism.

Thanks to Big Data, however, those arguments can be squashed much more easily. Using custom database software, physicians can directly model the negative effects of not having children vaccinated, and accurately estimate the number of preventable deaths that are caused by an unwillingness to seek this type of medical treatment. They can likewise dispute the claims that there exists any connection to autism. In fact, the website of the Mayo Clinic now bluntly dispels that. 

"Vaccines do not cause autism. Despite much controversy on the topic, researchers haven't found a connection between autism and childhood vaccines. In fact, the original study that ignited the debate years ago has been retracted. Although signs of autism may appear at about the same time children receive certain vaccines — such as the measles, mumps and rubella (MMR) vaccine — this is simply a coincidence," explains the site. 

This knowledge goes much further than a debate on television. A more thorough understanding of the benefits of vaccinations has been proven to save lives, and Big Data is helping to make that happen.

How Big Data changed Google’s workforce

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. 

Hadoop’s new release could have transformative impact

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. 

How big data can be used to overcome business mistakes

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.

Five tips for small retailers using Big Data

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. 

FileMaker could streamline hospital administration

In the past, health care was completely responsive. A patient would come in with a particular malady, a doctor would diagnose it as best as possible, and then they would set out on a course of treatment. Now, physicians are making a greater attempt to anticipate and react to health related issues, before they even rise to the level of requiring a clinical visit. 

For many doctors, Big Data can be an important part of those efforts. One of the primary issues in modern health administration is the sheer amount of infrastructure and scheduling necessary. Unlike the past, when a house visit could be made on a particular day, modern medicine necessitates a level of administration that can often be cumbersome. That is where analytics can come in. 

One of the problems that doctors face is coordinating records across multiple systems. Many things are done on paper and have to be scanned or filed by hand. By using the FileMaker service, however, they can better organize data and treat patients more effectively. 

There are ancillary benefits as well. By parsing the information and identifying trends, a physician can see which patients are likely to come back and how often, knowledge which can speed up their care process. In addition, they can pinpoint factors that are leading to recurrences, and note national health patterns before they reach the level of crises. It could even reduce the incidence of chronic diseases like diabetes and cancer, which tend to occur relatively more frequently in particular populations. 

As care gets more specialized, it will be fascinating to watch how doctors are able to implement new database technology into the age-old process of making people feel better. 

FileMaker could help determine which employees to promote

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. 

IBM’s Watson hopes to translate Big Data into sales

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.