Daniel Hodge is a mid-career Petroleum Industry professional.  He has formal training with a major IOC in the discipline of Reservoir Engineering and has worked in many of the major functional roles in upstream Petroleum Engineering ranging from managing a field crew offshore to building reservoir simulation models.  Daniel’s passion lies in applying Big Data Analytics to problem solving and value chain optimization and creation.  The petroleum industry has historically been one the industrial world’s primary necessitators of large scale computing power for the processing and interpretation of seismic data and the complex linear solvers used in reservoir simulation models.  Historically, working with these large datasets and buying the necessary computing power has been prohibitively expensive for anything other than niche applications with high potential for monetary reward. Today, these same practices can be applied to a much broader set of applications for business performance and optimization for little cost.  As both data measuring and data storage has increased exponentially the ability to effectively utilize this data has not kept pace.  Daniel believes the greatest near term value opportunities for both petroleum and non-petroleum companies lies in the ability of professionals to effectively manage their datasets, isolate the value components and translate this information into an impactful business understanding of performance and opportunities.  Herein lies the value in application of tool and skillsets reservoir engineers have been using for years to a broader set of business problems.