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The world’s information systems started generating 2.5 exabytes of data every day roughly a decade ago. Since then, that number has grown. Today, big data is growing increasingly important for enterprises. As the field matures, business leaders are looking for more effective ways to manage their information assets.

The ideal return on a big data project is $3.50 for every dollar invested into an initiative. However, many information projects yield a mere .50 cent return for each dollar spent. As a result, business leaders who yearn to leverage the benefits of big data technology are looking for ways to improve their return-on-investment. They know that the right planning will help them use big data systems to revolutionize their enterprises.

Although big data systems have been a hot topic among enterprise leaders for nearly a decade, most of the world’s massive information stores have just been created in the last few years. Much of this increase is due to advancements in mobile technology and social media platforms, and as the use of mobile technologies continues to increase among the global population, the amount of data generated every day will expand.

The new fountain of information made available by the Internet has empowered consumers with knowledge, and today’s big data systems deliver consumer metrics about their online activities in real time. As a result, business leaders are increasingly dependent on big data analysis to keep up with continually changing and growing consumer demands. Enterprise leaders want to harness this information to drive profits. However, forward-thinking leaders must take the right steps to produce meaningful results with their big data initiatives.

Benefits and Challenges of Big Data

Big data encompasses all the information acquired by an organization. Enterprises have come a long way from not having enough data, to having a seemingly insurmountable amount of information to manage.

For-profit and nonprofit enterprises want to make the most of their intellectual assets. Today’s organizations need meaningful reports for making short- and long-term decisions. They want to process and analyze data assets in real time to extract value from their information stores.

Big data systems are complex. Their value lies in giving analysts the power to find potentially beneficial patterns among massive volumes of information. Today’s business leaders need convenient, personalized data visualizations to help them make competent decisions. They don’t care about the big data process, just the end results. Decision-makers do not want, nor need, to understand database structure, common storage mechanisms or algorithms. What they do need are fast answers to their organization’s most pressing problems. At the same time, they face the responsibility of ensuring consumer privacy while finding new frontiers of opportunity, as well as securing consumer information so that it doesn’t fall into the wrong hands.

Hire a Translator

To extract value from a big data project, decision-makers must be able to understand the resulting insights. Often, initiatives fail when data scientists attempt to communicate results to decision-makers. When executives don’t understand the result of big data reports, they are likely to disregard the information. In fact, only 18-percent of executives polled in a recent survey believe that their big data initiatives are effective. Resultingly, more organizations are employing translators to serve as a liaison between data scientists and decision-makers.

Data translators facilitate communication between data scientists and enterprise executives. They understand what businesses need to improve their operations, as well as how to communicate technical concepts to non-technical personnel.

Because of their knowledge in STEM sciences and business, translators understand the language and concerns of both data scientists and business executives. They are skilled at interpreting data in a way that correlates with business objectives. Translators understand what data scientists need to do their job, as well as what business leaders need to make decisions. Resultingly, they’re uniquely positioned to extrapolate insights from projects that information specialists and executives may not have considered, and they add value to big data initiatives that can help organizations achieve their goals.

Don’t Forget the Human Aspect of Big Data

The available skill set of stakeholders is an important consideration for big data projects. Often, big data initiatives require new technologies and practices. The skill set of stakeholders, either experienced or learned, impacts big data initiative outcomes.

New big data initiatives should include personnel training within the scope of the project. This reduces the learning curve when working with new technologies and methods. By preparing personnel to work with new big data resources, enterprise leaders can maximize the outcome of projects.

Big data systems are now part of the daily business landscape. Engineers are learning how to gather information from new resources such as dialog, biometric data and sensor feedback. As researchers find more ways to collect information, the size of the world’s data stores will expand. As this occurs, the speed at which information is gathered will also increase. While scientists are improving big data system capabilities for analyzing text-based information, a world of untapped potential exists for mining images, video and other media. However, with each new development comes new challenges to overcome.