Month: September 2013

The big data era can only go so far.

Businesses are using this concept to track more information as a means to benefit their organization, but, as is always the case in our society, we start to grow tired of an idea or trend after a while. Or, we try to generate innovative approaches at a particular concept. This is happening with big data, and the next leap in its usefulness may be "big little data."

What is that, you ask?

It's the idea of applying big data principles to smaller sets of information. There is a tremendous amount of small data sets across the business infrastructure and they have to be properly managed. If data is collected in volumes where it's manageable but the same big data principles are applied to its management, companies can control their information more effectively.

Robert Morton, a senior software engineer, wrote a piece concerning the next step in big data. His belief is that there will be two components of information management. One is big little data and the other is data integration, which refers to the combination of disparate data parts. 

"These two components come together in an interesting way," Morton wrote. "As with databases, data integration has been around for some time but has not evolved at the same pace as data management systems. Data integration is currently not suited to blending massive data sets with numerous small data sets, since a big bottleneck in data integration is in requiring human involvement to help identify the common facets between two otherwise unrelated data sets."

Integrating data will require the breakdown of information so it can be easily manageable. This is a challenge, but will ultimately lead to more successful information management efforts.

Remember, regardless of how you manage your information, you will need appropriate tools in place to improve the way it's handled. A custom database software system will go a long way toward allowing you to break your information down and make smart decisions based on its contents and organization. Managing information integration requires an understanding of what data needs to be processed and where it needs to go. A FileMaker-based system can provide users with the tools needed to accomplish this, among any other data management goals. This will be important as we move into the future of big data management. 

One of the more interesting aspects of big data and its rise in the business realm is its rapid growth in emerging markets. Much like mobility, the cloud and many other innovative business technologies of the past five or so years, big data caught on in more established markets first but is now making strides in other parts of the world. Technology producers understand this and those who profit off of tech trends are focusing their efforts on emerging markets to ensure they capitalize on revenue opportunities. 

The markets themselves are doing what they can to benefit from this. Many are embracing their increased interest in new technologies and are seeking new avenues to take their role in the global industry to new levels. Malaysia, for example, has truly accepted its responsibility in the big data industry and hopes to one day serve as a centralized hub for information processing around the world. 

The country's geographical location, open space, industry incentives and infrastructure already give it an advantage over many emerging markets, and perhaps some established ones as well. Datuk Seri Najib Tun Razak, Malaysia's Prime Minister, attended he Global Science and Innovation Advisory Council meeting in San Francisco this week and spoke about these advantages, although he did admit the country lacks adequate personnel to manage big data the way the country envisions.

"This is a new skill that we need as thousands of data scientists will need to be produced in Malaysia's quest to be a data management enter," he said.

He also spoke of companies local to the conference—particularly Silicon Valley startups—and their ability to assist with the future of innovation, even if they fail as organizations. He indicated he hoped Malaysia could follow a similar pattern. 

"They accept the culture of failure and risk-taking as part of gaining experience for future success," he said. "Nobody is penalized but instead the failure is being used to see what went wrong. In other words, they might fail once, they might fail twice but given the right set of circumstances and encouragement, they might succeed the third or fourth time."

He said Malaysia and other emerging economies in Asia don't have this luxury, but he believes his country's passion for innovation will allow it to increase its presence in the big data market and achieve its goals as a global leader.

This news is relevant to all organizations in an increasingly global marketplace. Relying on emerging economies like Malaysia to facilitate the management of information could provide numerous business benefits by building efficiency and increasing productivity. However, having the right system in place is crucial. FileMaker development can allow organizations to construct a cloud-based custom database management software system that can connect to various markets and communicate vital information in a short amount of time. This is a crucial tool for any company that wants to capitalize on emerging markets.

It's also important to consider the words of Malaysia's Prime Minister. A lack of sufficient data scientists is currently slowing down the country's growth in the data market. This can happen on a smaller scale at your organization, which is why a custom database system designed to easily manage data in a user-friendly interface is so valuable.

The concept of big data has been around for a number of years, and most organizations have learned how to leverage information into smart, profitable business decisions, but plenty of companies still struggle with the execution of information management strategies.

To maximize the impact of their information and to truly be successful as a business, organizations have to learn what roadblocks stand in the way between them and an effective big data strategy. An article in the online publication Health Data Management offers three possibilities: a failure to understand the right data management technologies, budgetary constraints and a lack of understanding of the breadth of big data possibilities.

While this article is focused on health care data, its principles can be applied in virtually every industry.

“Big data technologies offer a different model for managing, maintaining and mobilizing data,” the article says. “Implementing them provides an opportunity to look at the workload currently managed by those traditional – and possibly crumbling – environments in order to find ways to reach better outcomes more quickly and cost-effectively.”

So how do businesses clear these  hurdles? Finding the right technology is the most important component of a big data strategy, as it can help solve all three.

Consider FileMaker development. Using this platform to build data management tools can give you the functionality you need to properly monitor and process your seemingly endless volumes of information. A custom database software system is designed specifically for your operations, meaning it is the best solution for your needs.

FileMaker development can also help you get around budgetary concerns. While money is always a factor in any business decision, many FileMaker projects, particularly if you work with the right development firm, can be completed with less money and in a shorter amount of time than you might expect. FileMaker is a cost-effective platform designed to produce positive results and start delivering a return on investment right away.

Finally, the functionality of a FileMaker-based system will not only help you with your data management initiatives, it will allow you to do things with your information you may have never thought possible. A fully functional solution will let you collect, process and store information in a way that promotes efficiency and increases business productivity.

As the quantity versus quality debate continues to dominate big data discussions, it's important for information managers to take time to evaluate what separates the good from the bad. We all want good information, but which metrics do we use to determine the quality of our data? Perhaps the most important is relevance.

In the big data era, it has become increasingly common to sift through line after line of information to find exactly what we are looking for. We need data that's relevant to whatever task we are trying to complete. A social media marketer working on a Facebook campaign might not be interested in how consumers are behaving on Twitter, at least for the purpose of completing the task at hand. Determining productivity at branch A will require all information pertaining to that particular branch, and any data related to branch B will not help for this particular purpose. 

When relevant information is easy to be found, it can quickly be applied to the task at hand, improving operational efficiency and overall productivity. This was addressed in a recent article in the online publication Human IPO. Ayanda Dlamini, business development manager of LGR Telecommunications, spoke with the news source about the act of finding relevant information and the difficulties an organization can encounter when managing seemingly endless volumes of data. 

"Big data management is about managing the growing volumes, variety, velocity and complexity of global data to determine what customers are saying now, how market sentiments are changing, and how the business should react," Dlamini said. "Trends are key to understanding customer behavior effective use of big data depends on finding the now in structured and unstructured data."

While we know it's important to weed out irrelevant information and focus only on the data that can be directly applied to what we're doing, the question is, how do we do this in a quick and easy manner? This might not be accomplished via traditional technology, so custom FileMaker development is an ideal solution. Using the platform to develop a custom database software system can give users the ability to monitor information and sort it according to relevancy. This reduces time spent searching through massive quantities of irrelevant data and can significantly improve a number of business processes. 

The debate over quality versus quantity of data has raged for a number of years, and various industry leaders have questioned whether we should wait on implementing big data strategies until we figure out how to effectively manage that information. An article in Health Data Management echoes that sentiment, saying that big data can't truly be effective because we don't yet know what to do with all our information.

Brian Hopkins, the article's author, implies that we are going about creating big data all wrong.

"Here is what I mean. We all know that big data is getting bigger," he writes. "Awesome, but so what? Most firms I talk to have only a vague notion of what could be done with all this data, yet they are ramping up big investments in big data hoping to capture insight from new social and mobile data sets. After six months to a year of dinking around and being disappointed with their 'build big data and they will come' strategy, the business will stop funding things and IT will get another black eye. Nobody needs that."

He stresses that big data isn't really something that an organization implements, but rather a way of doing business that grows gradually. Slowly maximizing the value of information and allowing it to grow organically in a manageable environment is the key to long-term success.

Ultimately, the way to maximize the potential of your data management initiatives is to utilize the information you do have to the best of your ability. Even if you aren't exactly jumping in to collect massive volumes of data, you can still improve your operations by implementing solutions that capture what you do have. This can be done with a custom database software system.

Big data has helped us gain insights about every important area of our business. Analyzing information can help us determine how to communicate with customers and if we should implement any amendments to standard operations. It can also determine if there are any risks in our systems that could potentially compromise the integrity of the organization.

Cyber security is an increasingly big concern in today's always-connected information age. The digitization of our data has made it vulnerable for cyber attacks. As systems designed to store and protect information evolve, so do criminals who find new ways to infiltrate advanced security solutions. 

So what does a company do to protect its information? It takes that data and uses it as a weapon to fight cyber crime. Gaining insights into vulnerabilities and the activity of individuals your company interacts with can go a long way toward stopping any threat of a security breach. 

An article in the Tech Republic examines the rise of big data and the increased criminal activity to complement it. While companies understand information security is even more important given the volume of today's information, organizations that implement solutions to quickly and effectively analyze that data can make considerable strides against cyber crime.

"As big data continues to be a game-changer for businesses, the security risks become even greater," the article says. "Users are becoming alarmed about how much data is being collected, with whom the data is being shared and how it is being used. There is a clear need for better engagement among key stakeholders and joined-up thinking throughout organizations, from the Chief Marketing Officer's office to the IT department, with the adoption of clear guidelines and best practice on the usage, storage and transfer of data both inside and outside the business."

Fighting cyber crime requires quick action and the optimization of resources. If companies can't quickly find the information they are looking for, or if it isn't presented in a way that lends itself to easy analysis, fighting cyber crime will be difficult. Building a custom database software system will provide organizations with the tools they need to both better protect information and use it to strengthen their efforts against cyber criminals. FileMaker development can help alleviate the risks associated with growing data because systems made this way are flexible and can adjust to accommodate new needs. 

Optimization is one of the keys to business efficiency. For companies to be successful in any aspect of their operations, they have to maximize their potential. This principle applies everywhere, including data management. 

Data optimization means collecting all the information at your disposal and managing it in a way that works best for your organization. Your data has to live up to its potential.

A recent Forbes article addressed eight key elements of a "game-changing" big data strategy. One of the main points was optimization of data. John Foley, the article's author, suggests the growth of information volumes has increased the need for optimized data management.

"Data management is the bedrock of corporate IT implementation, but the influx of a thousand times more data has upped the game," Foley writes. "Exponential growth requires IT teams to rethink what's worked in the past and bring in new tools to optimize database workloads that are orders of magnitude greater than before."

The key ingredient of a data optimization strategy in a growing environment is a flexible solution that can scale and adapt to any drastic changes in management operations. If your system cannot naturally expand to handle more information, you won't get the most out of it.

This is why FileMaker development is so valuable. Using the FileMaker platform to build a solution to monitor, analyze, process and store information will give businesses the tools they need to successfully handle their data. A custom database software system can take your information extract the highest possible value.

Databases and spreadsheets are used in companies all across the world. While each of these systems seems like a simple solution, there are a number of ways that individual businesses can implement them and find service providers to partner with. One of the top solutions is FileMaker.

A recent eHow article explained why a number of companies are turning toward FileMaker as their relational database engine software. It features an easy to use interface to retrieve, store and organize data without losing its capacity to handle large amounts of information. The usability is not determined by the user's level of computer literacy but with how easy it can be picked up and mastered.

"Small businesses and other groups, organizations and individuals also have uses and needs for databases," the article reads. "FileMaker Pro's user interface makes it so that these smaller users, with little to no financial resources, can start a database of their own without having to invest too much money or effort."

This means businesses do not need to outsource the construction of a database to an expensive third party but can instead create something more easily that is internal.

FileMaker also has a mobile application version known as FileMaker Go, which allows businesses to use the system and pair it with mobility, another major trend in the corporate landscape.

With the help of an IT consulting firm that specializes in FileMaker development, businesses of any size can implement the database solution and make sure the entire team is on the same page.

Since its inception into the business mindset, big data has been a controversial subject. It's important to separate this from data itself. Everyone knows that information volumes are growing rapidly, but the idea of implementing a big data strategy has not always been met with resounding acceptance. A New York Times piece titled "Is Big Data an Economic Big Dud?" is just a sampling of this antagonistic viewpoint. 

However, media influence and the doubts of industry leaders have not had a negative impact on big data growth. In fact, it has had quite the opposite effect. According to a study conducted by NewVantage Partners, 68 percent of C-suite executives plan on making big data investments of $1 million or more this year. Only 33 percent reported such plans last year. Additionally, 88 percent of survey respondents said they plan on spending more than $1 million annually on big data by 2016.

This means businesses are realizing the importance of big data and the value of investing in strategies and solutions designed to help manage their information. Those who oppose the idea of big data will likely have to reverse their position in the coming years as data grows. In this case, the inability to properly manage a big data initiative could ultimately prove to be a competitive disadvantage.

So how does one get on board with big data? While this can vary depending on numerous factors pertaining to each individual business, having the right technology to process information is a universal need. Building a custom database software solution can help organizations properly manage growing amounts of information.

This blog has recently spent a considerable amount of time covering data governance, its relationship with big data and its impact on information quality. And while we are learning more about it all the time, we are still working to establish a true definition and the official role of those tasked with data governance. 

An article in the online publication Information Management attempts this by declaring data governance as the act of serving and protecting the organization. This makes sense to some extent. Data governance helps identify risk that can have severe consequences for the company and it also processes information in a way that best serves the business. For example, data governance can identify quality metrics to help with the sales and marketing teams.

This sounds simple, but as Michele Goetz, the article's author, points out, there's a bit more to it than that. For instance, one policy doesn't fit all when it comes to managing information. And, in many cases, data governance may only really mean to protect, because service is actually redundant.

Essentially, if there's a data governance plan in place that corrects mistakes and weeds out inappropriate information, there shouldn't be a need to spoon-feed certain individuals or departments with the information they need. Instead, a well orchestrated data governance plan will create an environment where users can extract information as needed. They will be trusted to use appropriate data because it is organized due to governance. 

"In the grand scheme of things for the enterprise, especially as a chief data officer, the responsibility is to executives," Goetz writes. "They need to trust the data. The controls and processes at an enterprise level are tailored to their needs and expectations of information. Yet, in the world of big data, empowerment of the business to outsource IT, the number of increasingly tech savvy business people, and the ability to serve creates a more faceted data strategy — in turn a multi-faceted need for data governance."

This actually puts a heavier burden of responsibility on data governance. Giving users the flexibility to extract information for individual needs can add new layers of operational efficiency, but any issues pertaining to poorly governed data could result in major consequences. Creating a custom database software system to manage information can help companies govern their data and improve the overall quality of decision making.