Big data makes us collect and work with a large volume and variety of data and apply massive data analysis on education. Based on the missions, techniques and reports of PISA, it can be worthy as the mirror of our large-scale of educational evaluation reform. This study applies PISA 2009 in Shanghai. The subjects contain 5,115 students in 152 schools who attended in PISA 2009. The methodology is hierarchical linear modeling (HLM) and we analyze that the effect on index of economics and social and cultural status, proportion of qualified teacher to reading literacy, mathematical literacy and scientific literacy. The results show there are differences among reading, mathematical and scientific literacy in schools. To each school, once index of economics and social and cultural status raise one single unit, the outcome of PISA will promote approximately five points. Index of economics and social and cultural status positively explains the relationship with the scores. The higher index of economics and social and cultural status students are, the better PISA they perform. In addition, when school employ high proportion of qualified teacher, the students’ performances in reading, mathematical and scientific literacy are better.