Author: Justin Hesser

You’d be hard-pressed to find a better motto for Calvin and Hobbes than “there’s treasure everywhere.” Bill Watterson, the strip’s artist, thought it fit so well that he even used it as the title for one of the comic’s collections. The eponymous line is spoken when Calvin, after digging in the yard for hours and finding nothing more than rocks, a weird root and some grubs, happily shows off his bounty.

This same sense of optimism can and should guide your company’s forays into the world of Big Data.

Large-scale projects are popping up that are designed to cull billions of interactions and speak to the greater human experience. However, that doesn’t mean that there isn’t a lot of value in smaller projects that you can do without a huge expenditure on infrastructure. With a small amount of FileMaker development, your business can begin getting valuable insights without needing to add an entirely new department to analyze it.

A recent article in Ad Age spoke to just how many insights can be yielded when you just start looking.

“There really is data everywhere that you can tap into right now that will help you understand how customers, suppliers and others view you, your company and your products,” writes author Jim Louderback.

Finding out more about your potential consumer base and how you can best serve them doesn’t have to be an endeavor that bankrupts you. Instead, you can grab a copy of FileMaker, roll up your sleeves and start digging in your own backyard. There could very well be buried treasure cleverly disguised as old rocks.

Today, more and more businesses are relying on Big Data to either keep pace with or gain an advantage on their competitors. Companies are better understanding the value that a CT FileMaker developer can add to their brand, between better understanding of their customer base and a better awareness of how they can best serve them. Now that these ideas are more mainstream, the next iteration of these principles will feature several exciting improvements. 

One facet to see growth will be in speed. It almost seems impossible that information could get any faster, but that's exactly what's happening. Companies like Hadoop and Apache Spark are releasing software that promises memory processing that will happen almost in real time, an astounding upgrade that will no doubt have impressive implications. For example, businesses that employ sensors (like weather applications) can receive up to millions of individual "events" per second. Being able to parse that data more quickly will lead to better analysis and more streamlined results. 

Not only will information be more swift, it will be of better quality. Data collection has already far surpassed the human capacity to manage it manually, so it's processed based on rules defined by programmers ahead of time. In general, this allows for decision making to be done at a higher level than ever possible. However, a small piece of erroneous data can wind up having a relatively large effect. Improving the information gathering process and quickly expurgating bad data points will have an exponential effects on the overall quality of the analysis.

This improvement will also lead to new possible applications. Various industries have already seen the value of Big Data, and as it becomes more reliable and widespread, that number will only increase. The help of FileMaker consultants means that now even small businesses can harness this power without requiring specialized infrastructure or data scientists. The democratization of Big Data could also lead to breakthroughs: the more people have access to a strategy, the more people will be able to improve it. 

As we head into the new year, the future of analytics is bright, indeed. Not only will these new applications make those businesses function better, they could also have a positive effect on health care, diet, food and entertainment. 

Humans are a social species, and those interactions are being captured by data.

The average person produces just under a terabyte of information per year, and that number is only going up. For perspective's sake, imagine writing out each binary decision—represented by a one or a zero—by hand. If you scribbled out the amount the we all produce yearly, it wouldn't just extend to Saturn, it would extend to Saturn and back 25 times. Represented by sheep, the collective amount of data produced by people annually would fill the universe snugly, without any gaps.

It puts the "big" in Big Data.

All of this communication has an ancillary effect: sociologists, once constrained to wonder what people were saying and extrapolate from limited data, now have access to a greater wealth of first hand knowledge than they could have ever imagined being possible. And that number is growing quickly. It's lead many researchers to strongly consider the role something as fundamentally nonacademic as social media could yield in terms of lasting insight. 

Take, for example, Jon Levin. The Stanford economist performed an investigation into the ways that vendors set prices on popular auction site EBay. By using custom web application development and the access he had to hundreds of thousands of decisions, he was able to parse out several important trends, which confirmed some theories of pricing but exposed some significant errors. By grounding a largely theoretical field in actually human interactions, he was able to improve both substantially. 

For his efforts, Levin was awarded a John Bates Clark Medal, the highest award given to an economist under 40. 

It's not an isolated achievement, either. A research team at Harvard was able to combine IRS data with school district information to map out the long term effects of being matched up with a good teacher during formative years. Not only did they find that it had an effect on college matriculation rates, it also had an impact on income and the neighborhood a student would eventually end up living in. 

This year, Raj Chetty, who led the study, also won a John Bates Clark Medal.

The takeaway here is clear: when focused through a sharp academic lens, what might seem like a sprawl of Big Data can yield some valuable insights. 

There's a misconception that analytics and intuition are inherently at odds. That once you've hired a Connecticut FileMaker developer and invested in the attendant software, there's no longer a place for the sort of shrewd decision-making that comes with first-hand experience. In fact, this couldn't be further from the truth: using Big Data can support and confirm intuition, and allow you to pursue the hypothetical to a degree that would otherwise not be possible. 

One of the most obvious uses for this sort of naturalistic insight is in choosing the right subject in which to apply analytics. You can't get data on everything, so deciding where the software would be best applied requires a keen understanding of the nuances of your company. 

One salient example of this wisdom is the Caesar's chain of casinos. CEO Gary Loveman noted that there was low customer loyalty across his properties and that the customer service experience could be improved. This tactic hadn't been attempted in the gaming industry, but Loveman had a hunch that it could be a valuable piece in the revenue puzzle. 

But he didn't stop there. Instead, he invested in long-term analytics projects that sought to parse out exactly where the "service profit chain" could be strengthened. Loveman also understood the importance of orienting and guiding your information processes, which is why he insists on a ROI calculation for these sorts of projects. If you don't know how to use it properly, all the data in the world is for naught.

In the end, FileMaker is a tool. It's an incredibly valuable and powerful one, to be sure, but it requires the right craftsman to get the best out of it. 

Choppy waters don't exactly have much in common with an office environment. One thing they do share, however, is that the principles behind Big Data can apply equally well to both. In fact, it was those ideas that propelled Larry Ellison to an incredible win in the America's Cup.

In a sense, it's not surprising that Ellison should have sought to marry analytics and sailing. His company, Oracle, is one of the biggest technology companies in the entire world. It was this savvy that he was able to apply to the design and tactics of his chosen boat for one of the most prestigious races in the world.

Oracle's victory was one for the use of analytics and custom database software. Both of its boats had hundreds of sensors, which recorded thousands of variables. Some of the data points were so discrete that they were measured six hundred times per minute. The sailors themselves were given electronic tablets to use, as well as wrist displays and wireless capabilities. All of this information allowed designers to better understand how the boat could handle different conditions, as well as how close it was to operating at peak efficiency at all times.

All of this data-gathering yielded some valuable insights. Instead of the longer 80-foot trimarans, the team deduced that 72 feet was the largest boat they could easily control. By deciding on a catamaran, they were able to achieve high speeds without sacrificing the necessary portability — boats must be capable of being transported in shipping containers and reassembled within two days. 

There's a valuable takeaway here, even for those not inclined towards the seas: the more information you can process and analyze, the more of an advantage you'll have. 

Having a working knowledge of analytics is quickly shifting from "quirky ancillary benefit" to "business essential." For some new industries, using Big Data principles is second nature. However, especially if you work in an older or more entrenched field, your company might be resistant to these changes, and may take some convincing. Here's how you can speed up that process.

Using the right terminology is key. While IT jargon might come as second nature to you, inundating the conversation with unfamiliar phrases is likelier to yield glazed-over faces than nods of agreement. Business terms can go a long way towards helping you explain your case, and it's hard to go wrong with everyday language. Instead of discussing the "volume acceleration of corporate data availability," try pointing out that your competitors know more about your customers than you do, and that's hard to beat.

Once you've figured out the language, build your case. You don't have to address every single problem that your company has — in fact, highlighting a concrete issue that can be solved through use of analytics can go much further than positing it as a panacea. For example, say you have a problem with customer retention: people are coming through and buying things, but they're not coming back frequently enough. You can sell Big Data as a way to identify exactly where you're losing the consumer so that you can patch up those gaps and increase revenue.

Finally, make sure you point out how simple it can be to implement. Once you know how to use FileMaker, it's easy to create databases and sift through data quickly, and the results can really boost your business.

Any company that isn't at least considering the use of Big Data puts itself in danger of falling behind the competition. It's hard to keep up if you're working with far less information than others in your industry, so keeping abreast of current trends is virtually imperative. If and when you do dive into the world of custom database software, it's important to be aware of the risks. Here are three of the big ones — and how you can navigate around them. 

1.) Dexterity loss

If you have multiple levels to your company, data has to scale to fit all of them.  In order for management to make accurate decisions, it needs to have immediate access to the information. At the same time, others in the organization need to be able to see relevant data as well, so that they can implement any changes made. Getting it from one branch of your business to another can cost valuable time.

To avoid this pitfall, carefully consider structure before you implement any sort of database. A mobile platform like FileMaker can help easily sync findings across devices, so it's just as easy to access from a worksite as it is behind a desk.

2.) Financial loss

There's not question about it, Big Data takes some initial capital. If not used properly, all the money used to set up the programs will largely be wasted. A company that isn't on the same page runs the risk of not fully investing in the principles, and not getting the most out of the entire process.

That's why it's so crucial to have a game plan before you begin spending money. FileMaker consultants can help make sure you get the most out of your software, and provide a course of action that sets your company up for success.

3.) Security Loss

The more data you're using, the more data is available to be hacked or otherwise compromised. Especially if you're in an industry, like healthcare, where information can be sensitive or proprietary, if not carefully guarded, there is an inherent risk of a security breach.

So, it's critical to know the rules of your industry before you begin collecting data points about your customers. Carefully research any laws or statutes, and consider investing in insurance to minimize your liability. Limit access to software to those that require access, and transparently disclose what data you collect, and what you use it for. 

Schools around the country have seen FileMaker support their education efforts, providing meaningful data on student achievement and helping teachers contextualize performance and provide help when necessary. But in order for the software to help students, they have to show up to school in the first place.

Can a database drag a student out of bed and into the classroom? Not quite, but it might be able to do the next best thing.

That's the ambition behind an initiative by the Arlington County school district. Administrators have tapped ten teams of data scientists to analyze anonymous information and extract any meaningful trends that could help them to address their dropout rate. A panel of educators and analysts will judge the most compelling submission and offer up a huge cash incentive: $10,000. 

Arlington's truancy rates aren't terrible: they've been slashed from 13 percent in 2008 to just 6 percent this year. But the county is anxious to do more, understanding that every student should be put in a position to succeed. Crowdsourcing insights from outside data teams is a step in that direction. 

"Increasingly, people are considering this [data] a public resource. At the end of the day, it was created with public dollars," said Chris Kingsley, a policy analyst at the Data Quality Campaign. "If we can publish it and let other people come in and look at it, we can derive more value out of this data."

The teams will get access to information on assessment scores, schools attended, courses taken, grades, absences, demographic information and graduation status. If they're able to extract salient takeaways, it could push Arlington County's dropout rate even lower, a powerful benefit in its goal of providing a quality education for every student. 

Amassing a fortune is difficult, to be sure. For the philanthropically minded, donating it in the most conscientious possible manner is a struggle all its own. 

It was Andrew Carnegie who noted that it was harder to give money away intelligently than make it in the first place. And that problem isn't any easier now than it was when he was alive: there are some two million nonprofits in the U.S. today, with diverse and passionately stated missions. The question, then, becomes two fold. How can foundations best decide which charities to support, and how can those charities best address their chosen issues?

Big data could help provide answers to both. 

By gathering and analyzing more information than possible before, organizations can quickly identify which part of their missions are working, and which need to be updated. It's easier for them to understand how effective they are at creating change, and introduces a variety of new metrics by which they can measure success. For the donor's part, this new transparency can clue them in to which charities are doing the best and most efficient work, and provide a greater clarity on where exactly their money is going to go. 

Additionally, there's a great potential for cooperation across non-profits. While one might not have the infrastructure necessary to collect large-scale data, a few could make decisions based on the same information. One organization's investment in custom web application development could have a rippling effect. For example, if one group was working to make education more accessible, and another was focused on delivering medical supplies, the overlap of those two issues would lend themselves to collaboration. Demographic data could be shared across platforms, and allow both to work more efficiently. 

As is the case in other industries, it's important for charities and donors to understand how to use the information they collect. The first step in that is analyzing where it comes from: if the sample base is skewed, it could provide inaccurate results. In addition, knowing how to analyze the data found is a crucial step in finding it useful: for small nonprofits, this could mean training new staff on how to interpret data, or hiring a consultant to help manage it. 

While it will still take shrewd planning and keen intuition to solve the problems of society, Big Data can be an important tool in those efforts. 

Not only is Big Data growing, it's flourishing. 

That's the implication behind predictions released by IDC and the International Institute of Analytics (IIA), networks of industry experts who work to track developments and project future changes. The former projected that the market for Big Data will climb over $16 billion next year, a growth rate 6 times that of the overall IT market. This increase will be spread out between services (like FileMaker support), software and infrastructure. 

For the IIA, the future of the industry is in value. Now that it has the ability to bring together all of this new information, companies will want to focus on demonstrable advantages. This could lead to changes in business practices, creating process that better make use of these new technological opportunities. The institute also noted that there was something of a lack of talent when it comes to high level analytical ability, which led them to make further predictions about how businesses will get the most value. 

One projection is that managers would focus on developing their internal capacities to handle information, as well as setting in place processes to increase cooperation across departments. Companies that are unable to scale might then look to outside help, where "ready-made analytics" services can help otherwise lagging businesses get the advantages of Big Data.

A related prediction from IDC is that investors will focus on applications. One example is the healthcare industry, which has been making overtures towards using Big Data for some time, and appears poised for an information revolution of sorts. 

Whether or not these specific predictions come true, one thing seems clear: Big Data is the future, and it's not going anywhere.