We have gobs of data, nearly limitless cloud compute, and ever-improving machine learning algorithms, so what on earth is holding companies back from succeeding with big data? "Talent, talent, talent," says Dr. Kirk Borne. "The limiting factor is talent." To be sure, Borne has done more than most when it comes to fostering data science talent. Fourteen years ago, before his recent stint at Booz Allen Hamilton or his new gig at DataPrime, Borne helped create the nation's first data science degree program at George Mason University.

Dr. Kirk Borne is the Principal Data Scientist and an Executive Advisor at global technology and consulting firm Booz Allen Hamilton. In those roles, he focuses on applications of data science, data management, machine learning, A.I., and modeling across a wide variety of disciplines. He also provides training and mentoring to executives and data scientists within numerous external organizations, industries, agencies, and partners in the use of large data repositories and machine learning for discovery, decision support, and innovation. Previously, he was Professor of Astrophysics and Computational Science at George Mason University for 12 years where he did research, taught, and advised students in data science. Prior to that, Kirk spent nearly 20 years supporting data systems activities on NASA space science programs, which included a period as NASA's Data Archive Project Scientist for the Hubble Space Telescope.

Kirk Borne, principal data scientist at Booz Allen Hamilton, gave a keynote presentation at this year's Oracle Code One Conference on how the connection between emerging technologies, data, and machine learning are transforming data into value. Borne explained that with IoT, the value is not in all of the data produced, but instead in the contextual knowledge that sensors give us about the world. With IOT and context knowledge, the goal is to discover and deliver value from data. Value from data is achieved by going from understanding to actions. Emerging technological innovations like AI, robotics, computer vision and more, are enabled by data and create value from data.

Understanding big data and artificial intelligence is not something reserved for computer scientists, said Kirk Borne, principal data scientist for the international consulting firm, Booz Allen Hamilton. Manipulating massive amounts of data that are becoming available will affect every form of intellectual and business pursuit. "Data literacy is a way of thinking, not a thing to think about," Borne told attendees of BDA Edcon, the International Big Data and Analytics Education Conference hosted by University of Maryland University College on June 3 and 4. The conference explored how the convergence of big data analytics, artificial intelligence and cognitive computing can be implemented into teaching and learning experiences today to meet industry demand. The two-day event included the final judging and presentation of awards for the annual Global Analytics Competition. Data literacy is "a way of business, a way of doing whatever we do in the world. It really is for everyone, not just for data scientists," according to Borne.

"Practical AI" might seem like an oxymoron to some. But that's only if you view artificial intelligence as a futuristic and unrealistic pursuit. Kirk Borne, PhD, decidedly does not. Borne is the Principal Data Scientist and an Executive Advisor at global technology and consulting firm Booz Allen Hamilton. In this interview, Borne describes a number of practical AI applications in use today and offers tips on how to deploy AI for data scientists and nontechnical users. Borne will be attending SAS Global Forum this week, and we look forward to hearing more from him there.

In his role as principal data scientist at consulting firm Booz Allen Hamilton Inc., Kirk Borne sees the world in terms of data connections. "Life is about who is connected to whom and what is connected to what," Borne said, and he pointed to graph databases and graph analytics applications as new ways to capitalize on such connections. That's because graph databases, a form of NoSQL software, document the connections between data points quite different compared to mainstream relational databases. Graph systems represent data not as elements in tables, but as nodes linked to one another by edges with a set of properties that delineate the relationship between nodes. Therefore, one of the advantages of graph databases is they allow data analysts to navigate through data sets without the need to create and run complex queries to join combinations of tables together, as in the relational model.

In this article, Part 1 of the latest in his series exclusive to Data Makes Possible, Dr. Kirk Borne, Principal Data Scientist for Booz Allen Hamilton, explains the importance and value proposition of improving the human experience in the digital enterprise, and why the year of experience must include customers, end-users, employees, and any other stakeholders. A few years ago, I heard someone describe their data product in this way: "analytics at the speed of your business." Well, no disrespect intended, but I think they got the message backwards. Because business is no longer able to keep up with the flood of data that is coming in, from forces and sources everywhere: social, mobile, internet, intranet, images, video, audio, and documents. Consequently, what you really need is business at the speed of your data!

Adding artificial intelligence, machine learning, and other cognitive interactions to traditional business processes and applications enables greatly improved user experience and productivity. These technologies are already impacting all levels of business including finance, marketing, human resources, and sales. Proponents point to incremental changes in the way we work with AI and ML. But larger implementations are also taking hold. The New York Metropolitan Transit Authority (MTA) is using machine learning to understand rider patterns and will be changing color coding of their maps to help commuters and tourists get to their destinations faster.

We have heard terms like'artificial intelligence' and'machine learning' bandied about often, but do we really know what they hold for us in the coming days? Data Science may have become hot in this decade, but its existence can be traced back to more than a couple of decades ago. A lot of academic research took place in data science (data mining) then, but there was no application in the market; it was all theoretical and mathematical. Kirk Borne, Principal Data Scientist and Executive Advisor at Booz Allen Hamilton, shared some nuggets of wisdom in the field of data analytics and prediction, at the recently concluded DataHack Summit. Given his experience in the field of astrophysics, he emphasised the need for companies and individuals to be inspired and illuminated in the world of analytics. Borne believes that the following 10 trends would shape the future of data analytics.

In this article, Part 1 of the latest in his series exclusive to Data Makes Possible, Dr. Kirk Borne, Principal Data Scientist for Booz Allen Hamilton, explains the importance and value proposition of improving the human experience in the digital enterprise, and why the year of experience must include customers, end-users, employees, and any other stakeholders. A few years ago, I heard someone describe their data product in this way: "analytics at the speed of your business." Well, no disrespect intended, but I think they got the message backwards. Because business is no longer able to keep up with the flood of data that is coming in, from forces and sources everywhere: social, mobile, internet, intranet, images, video, audio, and documents. Consequently, what you really need is business at the speed of your data!