Decisions about installations of pipelines in gas industry determine the directions and course of billion rupees every year. The complexity of decision can range from simple to complex but analytical. These decisions determine cost of installation, operational optimization, timing of increasing facility capacity and long term utilization of pipeline. The complicated decisions within a company can take months of preparation. This paper addresses the mechanism to introduce decision trees (data mining) in pipeline industry to optimize the decisions.