The trucking sector dominates the commercial transportation industry with more than 80% of the total revenue, and it is expected to grow 21% in the next 10 years. If we consider the enormous amount of data generated by the trucking industry, it becomes clear that there should be a clearly developed framework for generating, acquiring, and analyzing data for stakeholders to capitalize on. The framework generated in this project is specifically for small trucking companies. The framework indicates the methods to generate data, including: Enterprise data and Internet of Things; the process to Acquire Data, including GPS, sensors, cameras, internal HR and accounting software, etc. The methods are followed by the transmission and pre-processing of the data, explaining the importance of... integrating and cleaning the data; the phases of Data Storage indicating the importance of Cloud Computing in today’s organizations and its advantages and disadvantages. Finally, the framework presents different ways to analyze the data: from simple descriptive statistics, predictive analytics to the most complex prescriptive analysis, depending on the type of data and the benefits organizations desired to gain. After the framework was developed, the research include a number of examples of software companies who provide Big Data analytic services, as well as, trucking companies who are already using Big Data analytics, and its impact in their operations. Including reduction in: fuel usage, maintenance costs, carbon dioxide emissions, and improvement in driver’s working conditions.