The design and implementation of higher level data flow programming language interfaces are becoming increasingly important for data intensive computation. DryadLINQ is a declarative, data-centric language that enables programmers to address the Big Data issue in the Windows Platform. DryadLINQ has been successfully used in a wide range of applications for the last five years. The latest release of DryadLINQ was published as a Community Technology Preview (CTP) in December 2010 and contains new features and interfaces that can be customized in order to achieve better performances within applications and in regard to usability for developers. This paper presents three design patterns in DryadLINQ CTP that are applicable to a large class of scientific applications, exemplified by SW-G, Matrix-Matrix Multiplication and PageRank with real data.