Wireless Sensor Network (WSN) plays a significant role in Internet of Things (IoT) and it incorporated to the physical atmosphere for observing the parameters like temperature, pressure and so on. The nodes in WSN are limited interms of energy, storage, bandwidth and computation. As the communication cost is greater when compared to sensing and processing cost, a number of data compression models are applied to minimize the quantity of data being forwarded in the network. This paper introduces a new Bit Reduction with Burrows Wheeler Transform called BR-BWT based data compression technique in WSN. The presented BR-BWT model performs encoding of data in two ways namely bit reduction using codeword allocation and BWT based encoding processes. Initially, a bit reduction process takes place using predefined codeword allocation process to determine the codeword for every character in the WSN data. Besides, the BWT based compression process takes place to further compresses the bit reduced data. To validate the performance of the BR-BWT model, a real time WSN dataset is tested and the results are discussed under diverse aspects.